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Advances in Computational Intelligence. MICAI 2023 International Workshops : 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 : 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 |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (475 pages) |
| Disciplina | 006.3 |
| 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. | UNINA-9910805570203321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 | ||
| ||
Automatic Syntactic Analysis Based on Selectional Preferences / / by Alexander Gelbukh, Hiram Calvo
| Automatic Syntactic Analysis Based on Selectional Preferences / / by Alexander Gelbukh, Hiram Calvo |
| Autore | Gelbukh Alexander |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (VIII, 165 p.) |
| Disciplina | 006.35 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Computational linguistics Natural language processing (Computer science) Artificial intelligence Computational Intelligence Computational Linguistics Natural Language Processing (NLP) Artificial Intelligence |
| ISBN | 3-319-74054-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- First approach: sentence analysis using rewriting rules -- Second approach: constituent grammars -- Third approach: dependency trees -- Evaluation of the dependency parser -- Applications -- Prepositional phrase attachment disambiguation -- The unsupervised approach: grammar induction -- Multiple argument handling -- The need for full co-occurrence. |
| Record Nr. | UNINA-9910299944703321 |
Gelbukh Alexander
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||