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Advances in Computational Intelligence [[electronic resource] ] : 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13–18, 2023, Proceedings, Part I / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, Hiram Ponce
| Advances in Computational Intelligence [[electronic resource] ] : 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13–18, 2023, Proceedings, Part I / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, Hiram Ponce |
| Autore | Calvo Hiram |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (363 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
Martínez-VillaseñorLourdes
PonceHiram |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Database management Application software Artificial Intelligence Computing Milieux Database Management System Computer and Information Systems Applications |
| ISBN | 3-031-47765-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Machine Learning -- Stock Market Performance Analytics Using XGBoost -- 1 Introduction -- 2 Related Work -- 3 Methodology and Development -- 3.1 Dataset Description -- 3.2 Data Preparation -- 3.3 Using XGBoost for Stock Trend and Prices Prediction -- 3.4 Moving Average -- 4 Results and Discussion -- 4.1 Correlation of Stock -- 4.2 XGBoost Regressor -- 4.3 MACD -- 5 Conclusion -- References -- 1D Quantum Convolutional Neural Network for Time Series Forecasting and Classification -- 1 Introduction -- 2 Preliminaries -- 2.1 Quantum Computation -- 2.2 Quantum Circuits -- 2.3 Variational Quantum Circuits -- 3 1D Quantum Convolution -- 4 Results and Discussion -- 4.1 Time Series Forecasting -- 4.2 Time Series Classification Using PTB Dataset -- 5 Conclusions -- References -- Hand Gesture Recognition Applied to the Interaction with Video Games -- 1 Introduction -- 2 Methodology -- 2.1 Hand Gesture Recognition -- 2.2 Video Game Application -- 3 Results -- 4 Conclusions and Future Work -- References -- Multiresolution Controller Based on Window Function Networks for a Quanser Helicopter -- 1 Introduction -- 2 Application of the Control Scheme to the Helicopter Model -- 2.1 Dynamic Identification -- 2.2 Proportional Multi-resolution Controller -- 2.3 Autotune of the Gains -- 3 Results -- 3.1 Open-Loop Simulation Results: Identification Process -- 3.2 Closed-Loop Simulation Results -- 3.3 Comparative Between PMR and PID Controllers -- 4 Conclusions and Future Work -- References -- Semi-supervised Learning of Non-stationary Acoustic Signals Using Time-Frequency Energy Maps -- 1 Introduction -- 2 Methods -- 2.1 STFT Maps -- 2.2 Dimensionality Reduction Using PCA -- 2.3 Background Subtraction -- 3 Description of Proposed Method -- 4 Acoustic Non-stationary Signals.
4.1 Signals Acquisition -- 5 Classifier Results -- 5.1 Training and Classification -- 6 Conclusion -- References -- Predict Email Success Based on Text Content -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Description of the Dataset -- 3.2 Building and Training the Model -- 3.3 Model Evaluation -- 4 Results and Discussion -- 5 Conclusions -- References -- Neural Drone Racer Mentored by Classical Controllers -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Neural Pilot -- 3.2 Proportional-Integral Controller -- 3.3 Model Predictive Controller -- 3.4 Active Disturbance Rejection Control -- 3.5 Training Process -- 4 Experimental Framework -- 5 Conclusions -- References -- Eye Control and Motion with Deep Reinforcement Learning: In Virtual and Physical Environments -- 1 Introduction -- 2 Proposed Solution -- 2.1 Deep Reinforcement Learning and the NN's Structure -- 2.2 Optimising the Learning Process -- 3 The Experiment -- 3.1 Optimizing Training with Image Detection -- 3.2 Testing with a Real Camera -- 3.3 Performance Metrics -- 4 Training Results and Discussion -- 4.1 Testing with a Real Camera -- 5 Conclusions -- References -- Fingerspelling Recognition in Mexican Sign Language (LSM) Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Data Capturing -- 3.2 Keypoints Detection -- 3.3 Keypoints Processing -- 3.4 Classification -- 4 Results -- 5 Conclusions -- References -- Load Demand Forecasting Using a Long-Short Term Memory Neural Network -- 1 Introduction -- 1.1 Artificial Neural Networks -- 2 Methodology -- 2.1 Data Provided by CENACE -- 2.2 LSTM Neural Network -- 2.3 Processing Data -- 2.4 Double-Input Long Short-Term Memory Neural Network -- 2.5 Triple-Input Long Short-Term Memory Neural Network -- 2.6 4-input Long Short-Term Memory Neural Network -- 2.7 Forecasting Errors -- 3 Results. 3.1 Double-Input LSTM -- 3.2 Triple-Input LSTM -- 3.3 Four-Input LSTM -- 4 Discussion and Conclusion -- References -- Computer Vision and Image Processing -- Benchmark Analysis for Backbone Optimization in a Facial Reconstruction Model -- 1 Introduction -- 2 Related Work -- 2.1 Face Reconstruction Models -- 2.2 Lightweight Backbone Architectures for Facial Reconstruction -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- T(G)V-NeRF: A Strong Baseline in Regularized Neural Radiance Fields with Few Training Views -- 1 Introduction -- 2 Related Work -- 2.1 Neural Radiance Fields -- 2.2 Training a NeRF with (very) Few Images -- 3 Proposed Regularization Framework -- 3.1 Depth Map Regularization -- 3.2 Second-Order Regularization -- 3.3 Occlusion Regularization -- 4 Experimental Results -- 4.1 Implementation Details -- 4.2 Ablation Results -- 4.3 Quantitative Results -- 4.4 Qualitative Results -- 5 Conclusions -- References -- Nonlinear DIP-DiracVTV Model for Color Image Restoration -- 1 Introduction -- 2 DIP-Reg Models for Color Image Restoration -- 2.1 DIP-Reg Models -- 2.2 Euclidean Models: DIP-TV and DIP-VTV -- 2.3 Riemannian Model: DIP-RiemannVTV -- 3 Dirac Vectorial Total Variations of a Color Image -- 3.1 The Euclidean Dirac Operator and Its Main Properties -- 3.2 Dirac Operators for Color Images -- 4 Experiments -- 4.1 Numerical Scheme -- 4.2 Application to Denoising -- 4.3 Application to Deblurring -- 5 Conclusion -- References -- An Efficient Facial Verification System for Surveillance that Automatically Selects a Lightweight CNN Method and Utilizes Super-Resolution Images -- 1 Introduction -- 2 Related Work -- 3 Super-Resolution Methods -- 4 Light Facial Verification Methods -- 5 Proposed Dynamic Scaling with Super-Resolution Methods -- 6 Proposed Lightweight Facial Verification System -- 7 Experiments. 7.1 Implementation Details -- 7.2 Datasets -- 7.3 Selection of Super-Resolution Method -- 7.4 Evaluation with the Custom Dataset -- 7.5 Evaluation of the LFVS with the Datasets -- 8 Discussion -- 9 Conclusion -- References -- Nonlinear L2-DiracVTV Model for Color Image Restoration -- 1 Introduction -- 2 The L2-VTV Model for Color Image Restoration -- 2.1 Variational Models for Image Restoration -- 2.2 The L2-VTV Model and Its Solutions -- 2.3 Primal-Dual Algorithm -- 3 Non Linear L2-DiracVTV Model for Color Image Restoration -- 3.1 Dirac Operators for Color Images -- 3.2 Weighted Dirac Operators for Color Images -- 3.3 Linear Weighted Dirac Vectorial Total Variation and Its Dual Formulation -- 3.4 Variational Models for Color Image Restoration -- 4 Experiments -- 4.1 On the Choice of the Color Space -- 4.2 Denoising -- 4.3 Deblurring -- 5 Conclusion -- References -- An FPGA Smart Camera Implementation of Segmentation Models for Drone Wildfire Imagery -- 1 Introduction -- 2 State-of-the-Art -- 2.1 Segmentation Models for Wildfire Detection and Characterization -- 2.2 Smart Camera Implementations for Computer Vision -- 3 Proposed Method -- 3.1 General Overview of the Optimization Approach -- 3.2 Dataset: Corsican Fire Database -- 3.3 Segmentation Model Training -- 3.4 Optimization -- 3.5 Proposed FPGA-Based Smart Camera System -- 4 Results and Discussion -- 4.1 Comparison Metrics -- 4.2 Quantitative Results -- 4.3 Qualitative Results -- 5 Conclusions -- References -- Intelligent Systems -- An Argumentation-Based Approach for Generating Explanations in Activity Reasoning -- 1 Introduction -- 2 Background -- 3 Proposal -- 3.1 Human Activity Framework and Local Selection -- 3.2 Global Selection -- 4 Generating Explanations -- 5 Theoretical Evaluation -- 6 Conclusions and Future Work -- References. A Decision Tree Induction Algorithm for Efficient Rule Evaluation Using Shannon's Expansion -- 1 Introduction -- 2 Background -- 3 Proposal -- 4 Experimental Results -- 5 Conclusions -- References -- Reasoning in DL-LiteR Based Knowledge Base Under Category Semantics -- 1 Introduction -- 2 Set-Theoretical Semantics of DL-LiteR -- 3 Category-Theoretical Semantics of DL-LiteR -- 4 Category-Theoretical Satisfiability for DL-LiteR -- 5 Conclusion -- References -- Applying Genetic Algorithms to Validate a Conjecture in Graph Theory: The Minimum Dominating Set Problem -- 1 Introduction -- 2 Background -- 3 The Conjecture to Be Verified -- 3.1 Generalized Quadrangle -- 3.2 The Minimum Dominating Set Problem -- 3.3 The Conjecture -- 4 Rank Genetic Algorithm for Finding Minimal Dominating Set -- 4.1 Solution Representation -- 4.2 Fitness Function -- 4.3 The Rank GA Operators -- 5 Results -- 6 Conclusions -- References -- Random Number Generator Based on Hopfield Neural Network with Xorshift and Genetic Algorithms -- 1 Introduction -- 2 NIST Testing Module -- 3 Related Works -- 3.1 Approaches Based on Chaotic Systems -- 3.2 Hybrid Pseudo Random Number Generator (PRNG) -- 3.3 Genetic Algorithms -- 4 PRNG Based on Hopfield Neural Network and Xorshift -- 5 PRNG Based on Genetic Algorithms -- 5.1 Selection -- 5.2 Loop -- 6 Tests and Results: PRNG Based on Hopfield Neural Network and Xorshift -- 6.1 Results of the NIST Module -- 6.2 Diehard Test Suite Results -- 7 Tests and Results: PRNG Based on Genetic Algorithms -- 7.1 Models to Compare with Ours -- 7.2 DieHarder Suite of Random Number Generator Tests -- 8 Discussion -- 9 Conclusion -- References -- Using Compiler Errors Messages to Feedback High School Students Through Machine Learning Methods -- 1 Introduction -- 2 Methodology -- 3 Classifier Development -- 3.1 Corpus Generation -- 3.2 Data Cleaning. 3.3 Vectorization. |
| Record Nr. | UNISA-996565870503316 |
Calvo Hiram
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Computational Intelligence : 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13–18, 2023, Proceedings, Part I / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, Hiram Ponce
| Advances in Computational Intelligence : 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13–18, 2023, Proceedings, Part I / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, Hiram Ponce |
| Autore | Calvo Hiram |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (363 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
Martínez-VillaseñorLourdes
PonceHiram |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Database management Application software Artificial Intelligence Computing Milieux Database Management System Computer and Information Systems Applications |
| ISBN | 3-031-47765-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Machine Learning -- Stock Market Performance Analytics Using XGBoost -- 1 Introduction -- 2 Related Work -- 3 Methodology and Development -- 3.1 Dataset Description -- 3.2 Data Preparation -- 3.3 Using XGBoost for Stock Trend and Prices Prediction -- 3.4 Moving Average -- 4 Results and Discussion -- 4.1 Correlation of Stock -- 4.2 XGBoost Regressor -- 4.3 MACD -- 5 Conclusion -- References -- 1D Quantum Convolutional Neural Network for Time Series Forecasting and Classification -- 1 Introduction -- 2 Preliminaries -- 2.1 Quantum Computation -- 2.2 Quantum Circuits -- 2.3 Variational Quantum Circuits -- 3 1D Quantum Convolution -- 4 Results and Discussion -- 4.1 Time Series Forecasting -- 4.2 Time Series Classification Using PTB Dataset -- 5 Conclusions -- References -- Hand Gesture Recognition Applied to the Interaction with Video Games -- 1 Introduction -- 2 Methodology -- 2.1 Hand Gesture Recognition -- 2.2 Video Game Application -- 3 Results -- 4 Conclusions and Future Work -- References -- Multiresolution Controller Based on Window Function Networks for a Quanser Helicopter -- 1 Introduction -- 2 Application of the Control Scheme to the Helicopter Model -- 2.1 Dynamic Identification -- 2.2 Proportional Multi-resolution Controller -- 2.3 Autotune of the Gains -- 3 Results -- 3.1 Open-Loop Simulation Results: Identification Process -- 3.2 Closed-Loop Simulation Results -- 3.3 Comparative Between PMR and PID Controllers -- 4 Conclusions and Future Work -- References -- Semi-supervised Learning of Non-stationary Acoustic Signals Using Time-Frequency Energy Maps -- 1 Introduction -- 2 Methods -- 2.1 STFT Maps -- 2.2 Dimensionality Reduction Using PCA -- 2.3 Background Subtraction -- 3 Description of Proposed Method -- 4 Acoustic Non-stationary Signals.
4.1 Signals Acquisition -- 5 Classifier Results -- 5.1 Training and Classification -- 6 Conclusion -- References -- Predict Email Success Based on Text Content -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Description of the Dataset -- 3.2 Building and Training the Model -- 3.3 Model Evaluation -- 4 Results and Discussion -- 5 Conclusions -- References -- Neural Drone Racer Mentored by Classical Controllers -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Neural Pilot -- 3.2 Proportional-Integral Controller -- 3.3 Model Predictive Controller -- 3.4 Active Disturbance Rejection Control -- 3.5 Training Process -- 4 Experimental Framework -- 5 Conclusions -- References -- Eye Control and Motion with Deep Reinforcement Learning: In Virtual and Physical Environments -- 1 Introduction -- 2 Proposed Solution -- 2.1 Deep Reinforcement Learning and the NN's Structure -- 2.2 Optimising the Learning Process -- 3 The Experiment -- 3.1 Optimizing Training with Image Detection -- 3.2 Testing with a Real Camera -- 3.3 Performance Metrics -- 4 Training Results and Discussion -- 4.1 Testing with a Real Camera -- 5 Conclusions -- References -- Fingerspelling Recognition in Mexican Sign Language (LSM) Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Data Capturing -- 3.2 Keypoints Detection -- 3.3 Keypoints Processing -- 3.4 Classification -- 4 Results -- 5 Conclusions -- References -- Load Demand Forecasting Using a Long-Short Term Memory Neural Network -- 1 Introduction -- 1.1 Artificial Neural Networks -- 2 Methodology -- 2.1 Data Provided by CENACE -- 2.2 LSTM Neural Network -- 2.3 Processing Data -- 2.4 Double-Input Long Short-Term Memory Neural Network -- 2.5 Triple-Input Long Short-Term Memory Neural Network -- 2.6 4-input Long Short-Term Memory Neural Network -- 2.7 Forecasting Errors -- 3 Results. 3.1 Double-Input LSTM -- 3.2 Triple-Input LSTM -- 3.3 Four-Input LSTM -- 4 Discussion and Conclusion -- References -- Computer Vision and Image Processing -- Benchmark Analysis for Backbone Optimization in a Facial Reconstruction Model -- 1 Introduction -- 2 Related Work -- 2.1 Face Reconstruction Models -- 2.2 Lightweight Backbone Architectures for Facial Reconstruction -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- T(G)V-NeRF: A Strong Baseline in Regularized Neural Radiance Fields with Few Training Views -- 1 Introduction -- 2 Related Work -- 2.1 Neural Radiance Fields -- 2.2 Training a NeRF with (very) Few Images -- 3 Proposed Regularization Framework -- 3.1 Depth Map Regularization -- 3.2 Second-Order Regularization -- 3.3 Occlusion Regularization -- 4 Experimental Results -- 4.1 Implementation Details -- 4.2 Ablation Results -- 4.3 Quantitative Results -- 4.4 Qualitative Results -- 5 Conclusions -- References -- Nonlinear DIP-DiracVTV Model for Color Image Restoration -- 1 Introduction -- 2 DIP-Reg Models for Color Image Restoration -- 2.1 DIP-Reg Models -- 2.2 Euclidean Models: DIP-TV and DIP-VTV -- 2.3 Riemannian Model: DIP-RiemannVTV -- 3 Dirac Vectorial Total Variations of a Color Image -- 3.1 The Euclidean Dirac Operator and Its Main Properties -- 3.2 Dirac Operators for Color Images -- 4 Experiments -- 4.1 Numerical Scheme -- 4.2 Application to Denoising -- 4.3 Application to Deblurring -- 5 Conclusion -- References -- An Efficient Facial Verification System for Surveillance that Automatically Selects a Lightweight CNN Method and Utilizes Super-Resolution Images -- 1 Introduction -- 2 Related Work -- 3 Super-Resolution Methods -- 4 Light Facial Verification Methods -- 5 Proposed Dynamic Scaling with Super-Resolution Methods -- 6 Proposed Lightweight Facial Verification System -- 7 Experiments. 7.1 Implementation Details -- 7.2 Datasets -- 7.3 Selection of Super-Resolution Method -- 7.4 Evaluation with the Custom Dataset -- 7.5 Evaluation of the LFVS with the Datasets -- 8 Discussion -- 9 Conclusion -- References -- Nonlinear L2-DiracVTV Model for Color Image Restoration -- 1 Introduction -- 2 The L2-VTV Model for Color Image Restoration -- 2.1 Variational Models for Image Restoration -- 2.2 The L2-VTV Model and Its Solutions -- 2.3 Primal-Dual Algorithm -- 3 Non Linear L2-DiracVTV Model for Color Image Restoration -- 3.1 Dirac Operators for Color Images -- 3.2 Weighted Dirac Operators for Color Images -- 3.3 Linear Weighted Dirac Vectorial Total Variation and Its Dual Formulation -- 3.4 Variational Models for Color Image Restoration -- 4 Experiments -- 4.1 On the Choice of the Color Space -- 4.2 Denoising -- 4.3 Deblurring -- 5 Conclusion -- References -- An FPGA Smart Camera Implementation of Segmentation Models for Drone Wildfire Imagery -- 1 Introduction -- 2 State-of-the-Art -- 2.1 Segmentation Models for Wildfire Detection and Characterization -- 2.2 Smart Camera Implementations for Computer Vision -- 3 Proposed Method -- 3.1 General Overview of the Optimization Approach -- 3.2 Dataset: Corsican Fire Database -- 3.3 Segmentation Model Training -- 3.4 Optimization -- 3.5 Proposed FPGA-Based Smart Camera System -- 4 Results and Discussion -- 4.1 Comparison Metrics -- 4.2 Quantitative Results -- 4.3 Qualitative Results -- 5 Conclusions -- References -- Intelligent Systems -- An Argumentation-Based Approach for Generating Explanations in Activity Reasoning -- 1 Introduction -- 2 Background -- 3 Proposal -- 3.1 Human Activity Framework and Local Selection -- 3.2 Global Selection -- 4 Generating Explanations -- 5 Theoretical Evaluation -- 6 Conclusions and Future Work -- References. A Decision Tree Induction Algorithm for Efficient Rule Evaluation Using Shannon's Expansion -- 1 Introduction -- 2 Background -- 3 Proposal -- 4 Experimental Results -- 5 Conclusions -- References -- Reasoning in DL-LiteR Based Knowledge Base Under Category Semantics -- 1 Introduction -- 2 Set-Theoretical Semantics of DL-LiteR -- 3 Category-Theoretical Semantics of DL-LiteR -- 4 Category-Theoretical Satisfiability for DL-LiteR -- 5 Conclusion -- References -- Applying Genetic Algorithms to Validate a Conjecture in Graph Theory: The Minimum Dominating Set Problem -- 1 Introduction -- 2 Background -- 3 The Conjecture to Be Verified -- 3.1 Generalized Quadrangle -- 3.2 The Minimum Dominating Set Problem -- 3.3 The Conjecture -- 4 Rank Genetic Algorithm for Finding Minimal Dominating Set -- 4.1 Solution Representation -- 4.2 Fitness Function -- 4.3 The Rank GA Operators -- 5 Results -- 6 Conclusions -- References -- Random Number Generator Based on Hopfield Neural Network with Xorshift and Genetic Algorithms -- 1 Introduction -- 2 NIST Testing Module -- 3 Related Works -- 3.1 Approaches Based on Chaotic Systems -- 3.2 Hybrid Pseudo Random Number Generator (PRNG) -- 3.3 Genetic Algorithms -- 4 PRNG Based on Hopfield Neural Network and Xorshift -- 5 PRNG Based on Genetic Algorithms -- 5.1 Selection -- 5.2 Loop -- 6 Tests and Results: PRNG Based on Hopfield Neural Network and Xorshift -- 6.1 Results of the NIST Module -- 6.2 Diehard Test Suite Results -- 7 Tests and Results: PRNG Based on Genetic Algorithms -- 7.1 Models to Compare with Ours -- 7.2 DieHarder Suite of Random Number Generator Tests -- 8 Discussion -- 9 Conclusion -- References -- Using Compiler Errors Messages to Feedback High School Students Through Machine Learning Methods -- 1 Introduction -- 2 Methodology -- 3 Classifier Development -- 3.1 Corpus Generation -- 3.2 Data Cleaning. 3.3 Vectorization. |
| Record Nr. | UNINA-9910760269403321 |
|
Calvo Hiram
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Computational Intelligence. MICAI 2023 International Workshops [[electronic resource] ] : WILE 2023, HIS 2023, and CIAPP 2023, Yucatán, Mexico, November 13–18, 2023, Proceedings / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, Hiram Ponce, Ramón Zatarain Cabada, Martín Montes Rivera, Efrén Mezura-Montes
| Advances in Computational Intelligence. MICAI 2023 International Workshops [[electronic resource] ] : WILE 2023, HIS 2023, and CIAPP 2023, Yucatán, Mexico, November 13–18, 2023, Proceedings / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, Hiram Ponce, Ramón Zatarain Cabada, Martín Montes Rivera, Efrén Mezura-Montes |
| Autore | Calvo Hiram |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (475 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
Martínez-VillaseñorLourdes
PonceHiram Zatarain CabadaRamón Montes RiveraMartín Mezura-MontesEfrén |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Software engineering Computer vision Computer science Data mining Application software Artificial Intelligence Software Engineering Computer Vision Theory of Computation Data Mining and Knowledge Discovery Computer and Information Systems Applications |
| ISBN | 3-031-51940-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Artificial intelligence. - Knowledge representation and reasoning -- Planning and scheduling -- Control methods -- Philosophical/theoretical foundations of artificial intelligence -- Computer vision -- Machine learning -- Symbolic and algebraic manipulation -- Simulation theory -- Robots -- Evolutionary computation -- Intelligent systems -- Natural language processing -- Bioinformatics -- Medical applications using AI. |
| Record Nr. | UNISA-996587864403316 |
|
Calvo Hiram
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Soft Computing : 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13-18, 2023, Proceedings, Part II / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, and Hiram Ponce
| Advances in Soft Computing : 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13-18, 2023, Proceedings, Part II / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, and Hiram Ponce |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2024] |
| Descrizione fisica | 1 online resource (348 pages) |
| Disciplina | 605 |
| Collana | Lecture Notes in Computer Science Series |
| Soggetto topico | Soft computing |
| ISBN | 3-031-47640-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Natural Language Processing -- Visualizing the Cosmos: A Novel Method for Text Recombination with Space News -- 1 Introduction -- 2 Dataset -- 3 Data Recombination Method -- 4 Experiments -- 5 Evaluation and Results -- 6 Conclusion -- References -- Propitter: A Twitter Corpus for Computational Propaganda Detection -- 1 Introduction -- 2 Related Work -- 3 The Construction of Propitter -- 3.1 Construction Methodology -- 3.2 Propitter Statistics -- 4 Experiments and Results -- 4.1 Baseline Results -- 4.2 On the Challenges of Propitter -- 5 Conclusions -- References -- Data Mining and Analysis of NLP Methods in Students Evaluation of Teaching -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Sampling and Participants -- 4 Results -- 4.1 Data Exploration -- 4.2 Results with TF-IDF Vectors -- 5 Discussion and Conclusion -- References -- Data Imputation with Adversarial Neural Networks for Causal Discovery from Subsampled Time Series -- 1 Introduction -- 2 Background -- 2.1 Causal Graphical Models for Time Series -- 2.2 Subsampling in Time Series -- 3 Related Work -- 3.1 PCMCI Algorithm -- 3.2 Deep Learning in Causal Discovery -- 3.3 Causal Discovery in Subsampled Time Series -- 4 Data Imputation for Causal Discovery of Time Series -- 4.1 Representation and Assumptions -- 4.2 Data Imputation -- 4.3 Generative Adversarial Model Architecture -- 4.4 Causal Structure Learning -- 5 Experimental Results -- 5.1 Experimental Setup -- 5.2 Experiment 1: Subsampled Time Series with the Same Noise Distributions -- 5.3 Experiments 2-5: Subsampled Time Series with Different Noise Distributions and Time Steps -- 5.4 Discussion -- 6 Conclusions and Future Work -- References.
Exploring the Challenges and Limitations of Unsupervised Machine Learning Approaches in Legal Concepts Discovery -- 1 Introduction -- 2 Theoretical Framework -- 3 Methodology -- 3.1 Data Source -- 3.2 Data Preprocessing -- 3.3 Topic Modelling Approach -- 3.4 Word Embedding Approach -- 3.5 Clusters Appraisal -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Large Sentiment Dictionary of Russian Words -- 1 Introduction -- 2 Related Works -- 3 Data and Method -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- An Interpretable Authorship Attribution Algorithm Based on Distance-Related Characterizations of Tokens -- 1 Introduction -- 2 State-of-the-Art -- 3 A Novel Embedding -- 4 Results -- 5 Conclusions and Discussion -- References -- Comparing Transformer-Based Machine Translation Models for Low-Resource Languages of Colombia and Mexico -- 1 Introduction -- 2 Indigenous Languages in this Research -- 3 Methodology -- 3.1 The Datasets Creation -- 3.2 Experimentation Setting -- 4 Results -- 4.1 Analysis of Results -- 5 Related Works -- 6 Conclusion -- 6.1 Future Work -- References -- Disaster Tweets: Analysis from the Metaphor Perspective and Classification Using LLM's -- 1 Introduction -- 2 Context and Motivation -- 2.1 Conceptual Metaphor -- 2.2 Large Language Models -- 3 State of the Art -- 4 Data Analysis -- 4.1 Dataset -- 4.2 Preprocessing -- 5 Models -- 5.1 BERT -- 5.2 RoBERTa -- 5.3 DistilBert -- 6 Results -- 7 Conclusion and Future Work -- References -- LLM's for Spanish Song Text Analysis and Classification Using Language Variants -- 1 Introduction -- 2 Motivation and Theoretical Concepts -- 2.1 Large Language Models -- 3 State of the Art -- 4 Datasets -- 5 Solution Proposal -- 5.1 Preprocessing -- 5.2 Classification -- 5.3 BERT-Base-Cased -- 5.4 RoBERTa-Base -- 5.5 DistilBERT-Base-Multilingual-Cased. 6 Results -- 7 Conclusions and Future Work -- References -- Bioinformatics and Medical Applications -- Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning*-1pc -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 Two-Step Transfer Learning -- 3 Results and Discussion -- 3.1 Two Step TL-Approach Results -- 3.2 Comparison with the State-of-the-art -- 4 Conclusion and Perspective -- References -- Automatic Assessment of Canine Trainability Using Heart Rate Responses to Positive and Negative Emotional Stimuli -- 1 Introduction -- 2 Methodology -- 2.1 Development of the Protocol for Dataset Generation -- 2.2 Experimental Procedure -- 2.3 Ethical Considerations -- 2.4 Obtained Dataset -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- LSTM-Based Infected Mosquitos Detection Using Wingbeat Sound -- 1 Introduction -- 2 Acoustic Chamber Design and Database Construction -- 2.1 Recording Condition and Dataset Construction -- 2.2 Proposed LSTM-Based Scheme -- 3 Experimental Results -- 4 Conclusions -- References -- FAU-Net: An Attention U-Net Extension with Feature Pyramid Attention for Prostate Cancer Segmentation -- 1 Introduction -- 2 State-of-the-Art -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Feature Pyramid Attention -- 3.3 Proposed Work -- 4 Results and Discussion -- 4.1 Quantitative Results -- 4.2 Qualitative Results -- 5 Conclusion -- References -- Implementation of a Digital Electromyographic Signal Processor Synthesized on an FPGA Development Board for Biocontrol Systems -- 1 Introduction -- 2 Related Work -- 3 Methods and Materials -- 3.1 Analog Signal Conditioning -- 3.2 Analog to Digital Conversion -- 3.3 Digital Filter -- 3.4 Signal Segmentation and Characteristic Extraction -- 3.5 Characteristic Classification -- 3.6 Module Integration and Implementation. 4 Results and Analysis -- 5 Conclusions and Future Work -- References -- BEC-1D: Biosignal-Based Emotions Classification with 1D ConvNet -- 1 Introduction -- 2 Related Works -- 2.1 Facial Gestures -- 2.2 EEG Signals -- 2.3 ECG Signals -- 2.4 GSR Signals and Multi-modal Emotion Recognition -- 3 Materials and Methods -- 3.1 Young Adult's Affective Data Dataset -- 3.2 1-D Convolutional Neural Networks -- 3.3 Performance Metrics -- 4 Proposal -- 4.1 Signal Preprocessing -- 5 Results -- 5.1 Validation Methods and Evaluation -- 5.2 Classification Results -- 6 Conclusions -- References -- Feature Selection and Classification for Searching Light at Night Exposure and Students' Weight Relationship -- 1 Introduction -- 2 Related Work -- 3 Data Description -- 4 Experiments -- 4.1 Experiments Design -- 4.2 Configuration Details of Experiments -- 5 Experiments Results -- 5.1 Results of Experiment 1 -- 5.2 Results of Experiment 2 -- 6 Conclusions and Future Work -- References -- PumaMedNet-CXR: An Explainable Generative Artificial Intelligence for the Analysis and Classification of Chest X-Ray Images -- 1 Introduction -- 2 Methodology -- 2.1 Model Architecture -- 3 Results -- 3.1 Latent Space Interpolation -- 3.2 Transfer Learning -- 3.3 Explainability -- 4 Summary and Conclusions -- References -- Robotics and Applications -- Visual Navigation Algorithms for Mobile Manipulators in Service Shops -- 1 Introduction -- 2 Industrial Challenge -- 3 The Problem Formulation -- 4 Development -- 4.1 Navigation -- 4.2 Vision -- 4.3 Object Manipulation -- 5 Results -- 6 Conclusion -- References -- NATLOC: Natural Language Object Localization -- 1 Introduction -- 2 Theory and Research -- 2.1 Image Generation -- 2.2 Image Matching Model -- 2.3 Reinforcement Learning -- 2.4 Differential Robot -- 3 Methodology -- 4 Results -- 4.1 Agent Training Results -- 5 Discussion. 6 Conclusion -- References -- Backup Solutions for the Refueling Problem in Foreign Transportation: A Case Study in Mexico -- 1 Introduction -- 1.1 Importance of Fuel -- 2 Transportation Model -- 2.1 Problem Statement -- 2.2 Mathematical Model -- 2.3 Example -- 3 Genetic Algorithm -- 3.1 Proposal -- 3.2 Additional Mutation -- 4 Numerical Results -- 5 Conclusion and Future Work -- References -- Self-location Algorithm for the Strategic Movement of Humanoid Robots -- 1 Introduction -- 2 Antecedents -- 3 Methods and Materials -- 3.1 Instruments -- 3.2 Process -- 4 Results -- 4.1 Execution Times -- 4.2 Confusion Matrix and ROC Curves -- 4.3 Performance Evaluation -- 5 Conclusions -- 6 Discussion -- A Additional Tables -- References -- Learning Neural Radiance Fields of Forest Structure for Scalable and Fine Monitoring -- 1 Introduction -- 2 Background -- 2.1 Neural Radiance Fields -- 3 Are Neural Fields Capable of Extracting 3D Structure in Forestry? -- 3.1 Terrestrial Imagery -- 4 Neural Radiance Fields: A Framework for Remote Sensing Fusion in Forestry -- 4.1 Filing in the Missing Below-Canopy Structure in ALS Data with TLS -- 4.2 Aerial Imagery -- 5 Prediction of Forest Factor Metrics -- 6 Conclusion -- References -- Edge AI-Based Vein Detector for Efficient Venipuncture in the Antecubital Fossa -- 1 Introduction -- 2 Literature Review -- 2.1 Image Acquisition Approaches -- 2.2 Computer-Based Vein Distribution Localization -- 2.3 Edge AI Methods -- 3 Material and Methods -- 3.1 Forearm Vein Segmentation -- 3.2 Cubital Fossa Localization -- 3.3 Hardware Development -- 4 Experimental Results -- 4.1 Forearm Vein Segmentation -- 4.2 Antecubital Fossa Localization -- 5 Conclusions and Future Work -- References -- Varroa Mite Detection in Honey Bees with Artificial Vision -- 1 Introduction -- 2 Related Works -- 3 Research Context -- 3.1 Bee Hive. 3.2 The Electrical Power Supply System. |
| Record Nr. | UNISA-996565870703316 |
| Cham, Switzerland : , : Springer, , [2024] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Soft Computing : 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13–18, 2023, Proceedings, Part II / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, Hiram Ponce
| Advances in Soft Computing : 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13–18, 2023, Proceedings, Part II / / edited by Hiram Calvo, Lourdes Martínez-Villaseñor, Hiram Ponce |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (348 pages) |
| Disciplina | 605 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Database management Application software Artificial Intelligence Computing Milieux Database Management System Computer and Information Systems Applications |
| ISBN | 3-031-47640-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Natural Language Processing -- Visualizing the Cosmos: A Novel Method for Text Recombination with Space News -- 1 Introduction -- 2 Dataset -- 3 Data Recombination Method -- 4 Experiments -- 5 Evaluation and Results -- 6 Conclusion -- References -- Propitter: A Twitter Corpus for Computational Propaganda Detection -- 1 Introduction -- 2 Related Work -- 3 The Construction of Propitter -- 3.1 Construction Methodology -- 3.2 Propitter Statistics -- 4 Experiments and Results -- 4.1 Baseline Results -- 4.2 On the Challenges of Propitter -- 5 Conclusions -- References -- Data Mining and Analysis of NLP Methods in Students Evaluation of Teaching -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Sampling and Participants -- 4 Results -- 4.1 Data Exploration -- 4.2 Results with TF-IDF Vectors -- 5 Discussion and Conclusion -- References -- Data Imputation with Adversarial Neural Networks for Causal Discovery from Subsampled Time Series -- 1 Introduction -- 2 Background -- 2.1 Causal Graphical Models for Time Series -- 2.2 Subsampling in Time Series -- 3 Related Work -- 3.1 PCMCI Algorithm -- 3.2 Deep Learning in Causal Discovery -- 3.3 Causal Discovery in Subsampled Time Series -- 4 Data Imputation for Causal Discovery of Time Series -- 4.1 Representation and Assumptions -- 4.2 Data Imputation -- 4.3 Generative Adversarial Model Architecture -- 4.4 Causal Structure Learning -- 5 Experimental Results -- 5.1 Experimental Setup -- 5.2 Experiment 1: Subsampled Time Series with the Same Noise Distributions -- 5.3 Experiments 2-5: Subsampled Time Series with Different Noise Distributions and Time Steps -- 5.4 Discussion -- 6 Conclusions and Future Work -- References.
Exploring the Challenges and Limitations of Unsupervised Machine Learning Approaches in Legal Concepts Discovery -- 1 Introduction -- 2 Theoretical Framework -- 3 Methodology -- 3.1 Data Source -- 3.2 Data Preprocessing -- 3.3 Topic Modelling Approach -- 3.4 Word Embedding Approach -- 3.5 Clusters Appraisal -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Large Sentiment Dictionary of Russian Words -- 1 Introduction -- 2 Related Works -- 3 Data and Method -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- An Interpretable Authorship Attribution Algorithm Based on Distance-Related Characterizations of Tokens -- 1 Introduction -- 2 State-of-the-Art -- 3 A Novel Embedding -- 4 Results -- 5 Conclusions and Discussion -- References -- Comparing Transformer-Based Machine Translation Models for Low-Resource Languages of Colombia and Mexico -- 1 Introduction -- 2 Indigenous Languages in this Research -- 3 Methodology -- 3.1 The Datasets Creation -- 3.2 Experimentation Setting -- 4 Results -- 4.1 Analysis of Results -- 5 Related Works -- 6 Conclusion -- 6.1 Future Work -- References -- Disaster Tweets: Analysis from the Metaphor Perspective and Classification Using LLM's -- 1 Introduction -- 2 Context and Motivation -- 2.1 Conceptual Metaphor -- 2.2 Large Language Models -- 3 State of the Art -- 4 Data Analysis -- 4.1 Dataset -- 4.2 Preprocessing -- 5 Models -- 5.1 BERT -- 5.2 RoBERTa -- 5.3 DistilBert -- 6 Results -- 7 Conclusion and Future Work -- References -- LLM's for Spanish Song Text Analysis and Classification Using Language Variants -- 1 Introduction -- 2 Motivation and Theoretical Concepts -- 2.1 Large Language Models -- 3 State of the Art -- 4 Datasets -- 5 Solution Proposal -- 5.1 Preprocessing -- 5.2 Classification -- 5.3 BERT-Base-Cased -- 5.4 RoBERTa-Base -- 5.5 DistilBERT-Base-Multilingual-Cased. 6 Results -- 7 Conclusions and Future Work -- References -- Bioinformatics and Medical Applications -- Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning*-1pc -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 Two-Step Transfer Learning -- 3 Results and Discussion -- 3.1 Two Step TL-Approach Results -- 3.2 Comparison with the State-of-the-art -- 4 Conclusion and Perspective -- References -- Automatic Assessment of Canine Trainability Using Heart Rate Responses to Positive and Negative Emotional Stimuli -- 1 Introduction -- 2 Methodology -- 2.1 Development of the Protocol for Dataset Generation -- 2.2 Experimental Procedure -- 2.3 Ethical Considerations -- 2.4 Obtained Dataset -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- LSTM-Based Infected Mosquitos Detection Using Wingbeat Sound -- 1 Introduction -- 2 Acoustic Chamber Design and Database Construction -- 2.1 Recording Condition and Dataset Construction -- 2.2 Proposed LSTM-Based Scheme -- 3 Experimental Results -- 4 Conclusions -- References -- FAU-Net: An Attention U-Net Extension with Feature Pyramid Attention for Prostate Cancer Segmentation -- 1 Introduction -- 2 State-of-the-Art -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Feature Pyramid Attention -- 3.3 Proposed Work -- 4 Results and Discussion -- 4.1 Quantitative Results -- 4.2 Qualitative Results -- 5 Conclusion -- References -- Implementation of a Digital Electromyographic Signal Processor Synthesized on an FPGA Development Board for Biocontrol Systems -- 1 Introduction -- 2 Related Work -- 3 Methods and Materials -- 3.1 Analog Signal Conditioning -- 3.2 Analog to Digital Conversion -- 3.3 Digital Filter -- 3.4 Signal Segmentation and Characteristic Extraction -- 3.5 Characteristic Classification -- 3.6 Module Integration and Implementation. 4 Results and Analysis -- 5 Conclusions and Future Work -- References -- BEC-1D: Biosignal-Based Emotions Classification with 1D ConvNet -- 1 Introduction -- 2 Related Works -- 2.1 Facial Gestures -- 2.2 EEG Signals -- 2.3 ECG Signals -- 2.4 GSR Signals and Multi-modal Emotion Recognition -- 3 Materials and Methods -- 3.1 Young Adult's Affective Data Dataset -- 3.2 1-D Convolutional Neural Networks -- 3.3 Performance Metrics -- 4 Proposal -- 4.1 Signal Preprocessing -- 5 Results -- 5.1 Validation Methods and Evaluation -- 5.2 Classification Results -- 6 Conclusions -- References -- Feature Selection and Classification for Searching Light at Night Exposure and Students' Weight Relationship -- 1 Introduction -- 2 Related Work -- 3 Data Description -- 4 Experiments -- 4.1 Experiments Design -- 4.2 Configuration Details of Experiments -- 5 Experiments Results -- 5.1 Results of Experiment 1 -- 5.2 Results of Experiment 2 -- 6 Conclusions and Future Work -- References -- PumaMedNet-CXR: An Explainable Generative Artificial Intelligence for the Analysis and Classification of Chest X-Ray Images -- 1 Introduction -- 2 Methodology -- 2.1 Model Architecture -- 3 Results -- 3.1 Latent Space Interpolation -- 3.2 Transfer Learning -- 3.3 Explainability -- 4 Summary and Conclusions -- References -- Robotics and Applications -- Visual Navigation Algorithms for Mobile Manipulators in Service Shops -- 1 Introduction -- 2 Industrial Challenge -- 3 The Problem Formulation -- 4 Development -- 4.1 Navigation -- 4.2 Vision -- 4.3 Object Manipulation -- 5 Results -- 6 Conclusion -- References -- NATLOC: Natural Language Object Localization -- 1 Introduction -- 2 Theory and Research -- 2.1 Image Generation -- 2.2 Image Matching Model -- 2.3 Reinforcement Learning -- 2.4 Differential Robot -- 3 Methodology -- 4 Results -- 4.1 Agent Training Results -- 5 Discussion. 6 Conclusion -- References -- Backup Solutions for the Refueling Problem in Foreign Transportation: A Case Study in Mexico -- 1 Introduction -- 1.1 Importance of Fuel -- 2 Transportation Model -- 2.1 Problem Statement -- 2.2 Mathematical Model -- 2.3 Example -- 3 Genetic Algorithm -- 3.1 Proposal -- 3.2 Additional Mutation -- 4 Numerical Results -- 5 Conclusion and Future Work -- References -- Self-location Algorithm for the Strategic Movement of Humanoid Robots -- 1 Introduction -- 2 Antecedents -- 3 Methods and Materials -- 3.1 Instruments -- 3.2 Process -- 4 Results -- 4.1 Execution Times -- 4.2 Confusion Matrix and ROC Curves -- 4.3 Performance Evaluation -- 5 Conclusions -- 6 Discussion -- A Additional Tables -- References -- Learning Neural Radiance Fields of Forest Structure for Scalable and Fine Monitoring -- 1 Introduction -- 2 Background -- 2.1 Neural Radiance Fields -- 3 Are Neural Fields Capable of Extracting 3D Structure in Forestry? -- 3.1 Terrestrial Imagery -- 4 Neural Radiance Fields: A Framework for Remote Sensing Fusion in Forestry -- 4.1 Filing in the Missing Below-Canopy Structure in ALS Data with TLS -- 4.2 Aerial Imagery -- 5 Prediction of Forest Factor Metrics -- 6 Conclusion -- References -- Edge AI-Based Vein Detector for Efficient Venipuncture in the Antecubital Fossa -- 1 Introduction -- 2 Literature Review -- 2.1 Image Acquisition Approaches -- 2.2 Computer-Based Vein Distribution Localization -- 2.3 Edge AI Methods -- 3 Material and Methods -- 3.1 Forearm Vein Segmentation -- 3.2 Cubital Fossa Localization -- 3.3 Hardware Development -- 4 Experimental Results -- 4.1 Forearm Vein Segmentation -- 4.2 Antecubital Fossa Localization -- 5 Conclusions and Future Work -- References -- Varroa Mite Detection in Honey Bees with Artificial Vision -- 1 Introduction -- 2 Related Works -- 3 Research Context -- 3.1 Bee Hive. 3.2 The Electrical Power Supply System. |
| Record Nr. | UNINA-9910760256603321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Challenges and Trends in Multimodal Fall Detection for Healthcare / / edited by Hiram Ponce, Lourdes Martínez-Villaseñor, Jorge Brieva, Ernesto Moya-Albor
| Challenges and Trends in Multimodal Fall Detection for Healthcare / / edited by Hiram Ponce, Lourdes Martínez-Villaseñor, Jorge Brieva, Ernesto Moya-Albor |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XIII, 259 p.) |
| Disciplina |
610.28
610.285 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico |
Biomedical engineering
Computational intelligence Biomechanics Biomedical Engineering and Bioengineering Computational Intelligence |
| ISBN | 3-030-38748-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Challenges and Solutions on Human Fall Detection and Classification -- Open Source Implementation for Fall Classification and Fall Detection Systems -- Detecting Human Activities based on a Multimodal Sensor Data Set using a Bidirectional Long Short-Term Memory Model: A Case Study -- Approaching Fall Classification using the UP-Fall Detection Dataset: Analysis and Results from an International Competition -- Reviews and Trends on Multimodal Healthcare -- A Novel Approach for Human Fall Detection and Fall Risk Assessment. |
| Record Nr. | UNINA-9910373903303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
NANOFIM 2018 : 2018 Nanotechnology for Instrumentation and Measurement : proceedings : 7-8 November 2018, Mexico City, Mexico / / edited by Hiram Ponce, Ramiro Velázquez, Zhidong Wang ; sponsored by Institute of Electrical and Electronics Engineers
| NANOFIM 2018 : 2018 Nanotechnology for Instrumentation and Measurement : proceedings : 7-8 November 2018, Mexico City, Mexico / / edited by Hiram Ponce, Ramiro Velázquez, Zhidong Wang ; sponsored by Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 |
| Descrizione fisica | 1 online resource (611 pages) |
| Disciplina | 620.5 |
| Soggetto topico |
Nanotechnology
Engineering instruments |
| ISBN | 1-5386-9161-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910318348903321 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
NANOFIM 2018 : 2018 Nanotechnology for Instrumentation and Measurement : proceedings : 7-8 November 2018, Mexico City, Mexico / / edited by Hiram Ponce, Ramiro Velázquez, Zhidong Wang ; sponsored by Institute of Electrical and Electronics Engineers
| NANOFIM 2018 : 2018 Nanotechnology for Instrumentation and Measurement : proceedings : 7-8 November 2018, Mexico City, Mexico / / edited by Hiram Ponce, Ramiro Velázquez, Zhidong Wang ; sponsored by Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 |
| Descrizione fisica | 1 online resource (611 pages) |
| Disciplina | 620.5 |
| Soggetto topico |
Nanotechnology
Engineering instruments |
| ISBN | 1-5386-9161-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996577918903316 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||