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Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part I
Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part I
Autore Choi Bong Jun
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (450 pages)
Altri autori (Persone) SinghDhananjay
TiwaryUma Shanker
ChungWan-Young
Collana Lecture Notes in Computer Science Series
ISBN 3-031-53827-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Natural Language and Dialogue Systems -- HGAN: Editable Visual Generation from Hindi Descriptions -- 1 Introduction -- 2 Background -- 2.1 Text-to-Image Generation -- 2.2 Attention -- 3 Material and Method -- 3.1 Architecture -- 3.2 Word-Focused Channel Attention -- 3.3 Editing Module -- 3.4 Objective Functions -- 3.5 Generator Objective -- 3.6 Discriminator Objective -- 4 Dataset -- 5 Implementation -- 6 Result -- 7 Component Analysis -- 8 Conclusion -- 9 Limitation and Future Work -- References -- Adopting Pre-trained Large Language Models for Regional Language Tasks: A Case Study -- 1 Introduction -- 2 Pre-trained Language Models -- 3 Preparation of Sentiment Analysis Dataset -- 4 Fine Tuning of Language Models -- 5 Related Work -- 6 Conclusion -- References -- Text Mining Based GPT Method for Analyzing Research Trends -- 1 Introduction -- 2 Related Research -- 2.1 Text Mining -- 3 Research Trend Analysis System Utilizing GPT Based on Text Mining -- 3.1 Keyword Extraction -- 3.2 Training GPT Models -- 3.3 Generate Sentences -- 4 Conclusion -- References -- Effect of Speech Entrainment in Human-Computer Conversation: A Review -- 1 Introduction -- 2 Fundamental Concept About Entrainment in Human-Human Conversation -- 3 Entrainment/Alignment Strategies Employed in Voice-Based Human-Machine Conversation and Their Impact on User Experience and Satisfaction -- 3.1 Acoustic-Prosodic Entrainment -- 3.2 Lexical Entrainment -- 3.3 Syntactic Alignment -- 4 Potential Benefits of Incorporating Entrainment in Voice-Based Human-Machine Conversation -- 4.1 Naturalness -- 4.2 Enhanced Trustworthiness -- 5 Summary and Future Prospect -- 5.1 Implementing Entrainment for Mechanomorphic Design -- 5.2 Manipulation of Temporal Aspects of the Machine to Provide Enhanced Turn-Taking.
5.3 Manipulation of Machine's Cues for Better Entrainment -- References -- HUCMD: Hindi Utterance Corpus for Mental Disorders -- 1 Introduction -- 2 Challenges -- 3 Related Work -- 4 Proposed Approach for HUCMD -- 4.1 Symptom Words -- 4.2 Intensity Words -- 4.3 Frequency Words -- 4.4 History Words -- 4.5 Actor Words -- 4.6 Trailer Words -- 4.7 Utterance Generation Algorithm -- 4.8 Generated Utterances -- 5 Dataset Validation -- 5.1 Bidirectional Long Short Term Memory (Bi-LSTM) -- 5.2 Convolution Neural Network -- 5.3 Network Architecture -- 5.4 Sampling Algorithm -- 5.5 Intent Detection -- 5.6 Slot Prediction -- 6 Conclusion -- References -- Classification of Cleft Lip and Palate Speech Using Fine-Tuned Transformer Pretrained Models -- 1 Introduction -- 2 Dataset -- 3 Methods -- 3.1 Wav2Vec2 -- 3.2 SEW -- 3.3 SEW-D -- 3.4 UniSpeechSat -- 3.5 HuBERT -- 3.6 DistilHuBERT -- 4 Experimentation and Results -- 5 Conclusion -- References -- Affective Computing and Human Factors -- Visual-Sensory Information Processing Using Multichannel EEG Signals -- 1 Introduction -- 2 Main Part -- 2.1 Significance of Analysis and Classification of EEG Signals -- 2.2 EEG Signal Processing Based on Brain Computer Interface -- 3 Conclusion -- References -- Vision Transformer-Based Emotion Detection in HCI for Enhanced Interaction -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Methodology -- 5 Evaluation Metrics -- 6 Experimental Results -- 7 Conclusion -- References -- GenEmo-Net: Generalizable Emotion Recognition Using Brain Functional Connections Based Neural Network -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Dataset Description -- 3.2 Data Preprocessing -- 3.3 Feature Extraction -- 3.4 Model Architecture -- 3.5 Model Evaluation -- 4 Results and Discussion -- 5 Conclusion -- References.
Ear-EEG Based-Driver Fatigue Detection System Augmented by Computer Vision -- 1 Introduction -- 2 Proposed System -- 2.1 Ear-EEG Embedded Device -- 2.2 Computer Vision-Based on Face Features -- 2.3 Experiment -- 2.4 Deep Learning Model -- 3 Results and Discussion -- 4 Conclusion -- References -- Cross Cultural Comparison of Emotional Functional Networks -- 1 Introduction -- 2 Methodology -- 2.1 Datasets -- 2.2 Complex Network Analysis of the Brain During Emotion -- 3 Results and Observations -- 4 Discussion -- References -- Emotion Recognition Using Phase-Locking-Value Based Functional Brain Connections Within-Hemisphere and Cross-Hemisphere -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Dataset Description -- 3.2 Data Preprocessing -- 3.3 Feature Extraction -- 3.4 Feature Selection -- 3.5 Classification -- 4 Results and Discussion -- 5 Conclusion -- References -- Context-Aware Facial Expression Recognition Using Deep Convolutional Neural Network Architecture -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Model Architectures -- 4 Experiments and Discussion -- 4.1 Benchmark Datasets: Emotic and CAER -- 4.2 Experimental Setup -- 5 Conclusions -- References -- Human Centred AI -- Exploring Multimodal Features to Understand Cultural Context for Spontaneous Humor Prediction -- 1 Introduction -- 2 Features and Model -- 2.1 Audio -- 2.2 Video -- 2.3 Text -- 2.4 Fusion -- 3 Experiments and Results -- 3.1 Experimental Setup -- 3.2 Dataset and Data Preparation -- 3.3 Hyperparameters -- 3.4 Results -- 3.5 Discussion -- 4 Conclusions and Future Work -- References -- Development of Pneumonia Patient Classification Model Using Fair Federated Learning -- 1 Introduction -- 2 Related Work -- 2.1 Federated Learning -- 2.2 DenseNet (Dense Convolutional Network) [18] -- 2.3 CheXNet [21] -- 2.4 Loss Function -- 2.5 IID, Non-IID Condition.
3 Improve Transparency -- 3.1 MINIMAR (MINImum Information for Medical AI Reporting): Reporting Standards for Artificial Intelligence in Health Care [26] -- 4 Method -- 4.1 Dataset -- 4.2 Data Pre-processing, Augmentation -- 4.3 FFLFCN (Fair Federated Learning Loss Function Chest X-ray Dense Convolutional Network) Model Construction -- 5 Results -- 6 Conclusion -- References -- Artificial Intelligence in Medicine: Enhancing Pneumonia Detection Using Wavelet Transform -- 1 Introduction -- 2 Related Works -- 3 Dataset Description/Methodology -- 4 Experiments and Results -- 5 Future Research Work -- 6 Conclusion -- References -- Maximizing Accuracy in AI-Driven Pattern Detection in Cardiac Care -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Pre-processing for Cardiac Data -- 3.3 Algorithm Utilized -- 4 Results -- 4.1 Model Building -- 4.2 Model Validation -- 5 Conclusion -- References -- Development of IMU Sensor-Based XGBoost Model for Patients with Elbow Joint Damage -- 1 Introduction -- 2 Development of IMU Sensor-Based XGBoost Model -- 3 Experiment and Results -- 4 Conclusion -- References -- Application of Daubechies Wavelets in Digital Processing of Biomedical Signals and Images -- 1 Introduction -- 2 Determining Daubechies Discrete Wavelet Transform Coefficients -- 3 Construction of One-Dimensional Wavelet Transforms -- 4 Identification of Wavelet Methods in Denoising in Tomographic Images -- 5 Conclusion -- References -- An Integrated System for Stroke Rehabilitation Exercise Assessment Using KINECT v2 and Machine Learning -- 1 Introduction -- 2 Materials and Methods -- 2.1 Used Device -- 2.2 Machine Learning Model Selection -- 2.3 KIMORE Dataset -- 3 Experimental Setup -- 3.1 Device Setup -- 3.2 Instructions and Guidelines -- 4 Results -- 5 Conclusion and Future Works -- References.
Gastric Ulcer Detection in Endoscopic Images Using MobileNetV3-Small -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 The Dataset -- 3.2 Preprocessing -- 3.3 Architecture and MobilenetV3-Small -- 3.4 Performance Metrics -- 4 Results -- 5 Conclusion -- References -- Exploring Quantum Machine Learning for Early Disease Detection: Perspectives, Challenges, and Opportunities -- 1 Introduction -- 2 Related Work -- 3 Quantum Machine Learning (QML) in Medical Applications -- 3.1 Quantum Software Platforms and Tools -- 3.2 Quantum Machine Learning Models -- 3.3 Quantum Computing Hardware -- 4 QML Algorithms -- 4.1 Quantum Neural Networks (QNN) -- 4.2 Quantum Boltzmann Machines -- 4.3 Quantum Support Vector Machines -- 5 Challenges for Medical Translation -- 5.1 Noise Tolerance and Mitigation -- 5.2 Problem-Aware Model Optimization -- 5.3 Workflow Integration Complexities -- 6 Final Discussion -- 7 Conclusions -- References -- Human-Robot Interaction and Intelligent Interfaces -- Subject-Independent Brain-Computer Interfaces: A Comparative Study of Attention Mechanism-Driven Deep Learning Models -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 Proposed Transformer Model Architecture -- 2.3 Model Selection -- 3 Results and Discussion -- 4 Conclusion -- References -- PPHR: A Personalized AI System for Proactive Robots -- 1 Introduction -- 2 System Architecture -- 2.1 Sensing -- 2.2 Learning -- 2.3 Interacting -- 3 Methodology -- 3.1 Reinforcement Learning -- 3.2 Personalization of Models -- 3.3 Federated Learning -- 3.4 Extensibility of Models -- 3.5 Activity State -- 4 Implementation -- 4.1 Model Structure -- 4.2 Data Collection -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Classifying Service Robots in Commercial Places Based on Communication: Design Elements by Level of Communication -- 1 Introduction.
2 Related Works.
Record Nr. UNINA-9910842287303321
Choi Bong Jun  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part II
Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part II
Autore Choi Bong Jun
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (355 pages)
Altri autori (Persone) SinghDhananjay
TiwaryUma Shanker
ChungWan-Young
Collana Lecture Notes in Computer Science Series
ISBN 3-031-53830-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- AI and Big Data -- Automated Fashion Clothing Image Labeling System -- 1 Introduction -- 2 Related Research -- 3 Fashion Clothing Image Labeling System -- 3.1 Dataset Collection -- 3.2 Image Preprocessing -- 3.3 Yolo Training and Labeling Results -- 4 Conclusion -- References -- AI-Based Estimation from Images of Food Portion Size and Calories for Healthcare Systems -- 1 Introduction -- 2 Dataset of Uzbek Foods -- 3 Proposed Method -- 4 Experimental Results and Analysis -- 5 Limitation and Future Work -- 6 Conclusions -- References -- Blockchain Technology as a Defense Mechanism Against Data Tampering in Smart Vehicle Systems -- 1 Introduction -- 2 Background and Literature Review -- 3 Data Tampering in Smart Vehicle Systems -- 4 Blockchain Technology as a Solution in Smart Vehicle Systems -- 4.1 Technical Foundations of Blockchain in Smart Vehicle Systems -- 4.2 Practical Implementations and Prototypes -- 5 Conclusion -- References -- Classification of Weeds Using Neural Network Algorithms and Image Classifiers -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Classification Models Architectures and Algorithms -- 4 Results -- 5 Future Scope and Conclusion -- References -- Weed and Crop Detection in Rice Field Using R-CNN and Its Hybrid Models -- 1 Introduction -- 2 Related Work -- 3 Methods and Materials -- 3.1 Experimental Site and Image Acquisition -- 3.2 Data Pre-processing -- 4 Weed Detection Method -- 4.1 Regions with RCNN -- 4.2 Regions with RCNN-LSTM -- 4.3 Regions with RCNN-GRU -- 5 Results and Discussions -- 6 Conclusion -- References -- Deep Learning -- Spatial Attention Transformer Based Framework for Anomaly Classification in Image Sequences -- 1 Introduction -- 2 Related Study.
3 Proposed Framework -- 3.1 Spatial Attention Module (SAM) -- 3.2 Shifted Window Transformer (SWIN) -- 3.3 SST for Anomaly Detection -- 4 Experimental Results and Discussions -- 4.1 Datasets -- 4.2 Results and Discussions -- 5 Conclusions -- References -- Development of LSTM-Based Sentence Generation Model to Improve Recognition Performance of OCR System -- 1 Introduction -- 2 Related Works -- 3 LSTM-Based Sentence Generation Model -- 3.1 Training Dataset -- 3.2 Implemented LSTM Model -- 4 Experiments and Results -- 5 Conclusion -- References -- Satellite Imagery Super Resolution Using Classical and Deep Learning Algorithms -- 1 Introduction -- 2 Background -- 2.1 Image Resolution -- 2.2 Interpolation for Image Enhancement -- 2.3 DWT and Noise Removal Techniques -- 3 Deep Learning Based Architectures for Image Super Resolution -- 3.1 High Level Architecture -- 3.2 Enhanced Deep Residual Networks for Single Image Super-Resolution(EDSR) -- 3.3 Wide Activation for Efficient and Accurate Image Super-Resolution(WDSR) -- 3.4 Deep Alternating Network(DAN) -- 4 Evaluation Metrics -- 5 Comparisons and Challenges -- 6 Comparisons and Challenges -- References -- Traffic Sign Recognition by Image Preprocessing and Deep Learning -- 1 Introduction -- 2 Related Works -- 2.1 Traditional Approach -- 2.2 Deep Learning Based Methods -- 3 Our Methodology -- 3.1 Dark Channel Prior Based Image Dehazing -- 3.2 Improved Detection Model -- 3.3 Data Augmentation -- 4 Experiments and Analysis -- 4.1 Results -- 4.2 Experimental Analysis and Discussion -- 5 Conclusion -- References -- Convolutional Autoencoder for Vision-Based Human Activity Recognition -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Convolutional Autoencoder (Conv-AE) -- 3.2 Convolutional Neural Network (CNN) -- 3.3 Pre-processing -- 3.4 Feature Representation -- 3.5 Classification.
4 Experimental Results -- 4.1 Datasets -- 4.2 Results and Discussions -- 5 Conclusions and Future Scope -- References -- Deep Learning Approach for Enhanced Object Recognition and Assembly Guidance with Augmented Reality -- 1 Introduction -- 2 Methodology -- 2.1 Dataset Collection and Image Pre-processing -- 2.2 Step Detection -- 3 Results and Discussion -- 3.1 Prototype -- 3.2 SSD Performance -- 3.3 YOLOv7 Performance -- 3.4 User Testing -- 4 Conclusion -- References -- 3D Facial Reconstruction from a Single Image Using a Hybrid Model Based on 3DMM and Deep Learning -- 1 Introduction -- 2 Related Work -- 2.1 3DMM-Based Methods -- 2.2 Image-Based Methods -- 3 Methodology -- 3.1 3D Morphable Model -- 3.2 Camera Model -- 3.3 Illumination Model -- 3.4 Model Fitting -- 4 Results Analysis -- 5 Conclusion -- References -- Human Activity Recognition with a Time Distributed Deep Neural Network -- 1 Introduction -- 2 Related Works -- 3 The Proposed Method -- 3.1 Input Dataset -- 3.2 Data Pre-processing -- 3.3 Time Distributed Frame Conversion -- 3.4 Time Distributed CNN Layers -- 3.5 LSTM Layers -- 3.6 Training and Testing -- 3.7 Evaluation -- 4 Experimental Results and Discussion -- 4.1 UCI Sensor Dataset [2] Results -- 4.2 OPPORTUNITY Sensor Dataset Results -- 5 Conclusions -- References -- Intelligent Systems -- Artificial Neural Network to Estimate Deterministic Indices in Control Loop Performance Monitoring -- 1 Introduction -- 2 Background -- 2.1 Control Performance Monitoring -- 2.2 CPM Performance Indices -- 2.3 Machine Learning -- 2.4 Control-Loop Performance Assessment Whit Machine Learning -- 3 Methodology -- 4 Results -- 4.1 The Model with Machine Learning -- 5 Conclusions -- References -- Interference Mitigation in Multi-radar Environment Using LSTM-Based Recurrent Neural Network -- 1 Introduction.
2 Signal Model and Interference Effect Analysis -- 3 LSTM-RNN Architecture -- 4 Methodology, Results and Discussions -- 5 Conclusions -- References -- Centrifugal Pump Health Condition Identification Based on Novel Multi-filter Processed Scalograms and CNN -- 1 Introduction -- 2 Experimental Setup -- 3 Proposed Framework -- 4 Results and Performance Evaluation -- 5 Conclusion -- References -- A Closer Look at Attacks on Lightweight Cryptosystems: Threats and Countermeasures -- 1 Introduction -- 1.1 Lightweight Cryptography -- 2 Related Work -- 2.1 Side-Channel Analysis and Countermeasures: -- 2.2 Light Lightweight Cryptographic Algorithm Design: -- 3 Types of Attacks on Cryptosystems -- 3.1 Passive Attacks -- 3.2 Active Attacks -- 4 Cryptographic Attacks -- 4.1 Ciphertext Only Attacks (COA) -- 4.2 Known Plaintext Attack (KPA) -- 4.3 Dictionary Attack -- 4.4 Brute Force Attack (BFA) -- 4.5 Man in Middle Attack (MIM) -- 5 Countermeasures for Lightweight Encryption -- 5.1 Fault Injection Attacks and Protections: -- 5.2 Post-quantum Lightweight Cryptography: -- 5.3 Energy-Efficient Cryptography: -- 5.4 Machine Learning and Lightweight Cryptography: -- 6 Conclusion -- References -- A Prototype of IoT Medication Management System for Improved Adherence -- 1 Introduction -- 2 The Design Methodology of an Innovative Pharmaceutical IoT Medication Product -- 2.1 External Technology of the Product -- 2.2 Internal Technology of the Product -- 2.3 Mobile Application to Control the Product -- 3 Prototype Development of an Innovative Pharmaceutical -- 4 Final Discussion -- References -- Mobile Computing and Ubiquitous Interactions -- Navigating the Complexities of 60 GHz 5G Wireless Communication Systems: Challenges and Strategies -- 1 Introduction -- 2 Weaknesses of the 60 GHz Massive MIMO System -- 3 Proposed Algorithm -- 3.1 Channel Model of Sparse Multipath.
3.2 SAMP Algorithm -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- A Survey on Channel Estimation Technique Classifications and Various Algorithms -- 1 Introduction -- 2 Channel Estimation -- 2.1 Channel Estimation Classification -- 2.2 Channel Estimation Algorithms -- 3 Discussions and Future Research -- References -- Wearable-Based SLAM with Sensor Fusion in Firefighting Operations -- 1 Introduction -- 2 Method -- 2.1 System Overview -- 2.2 Map Points Calculation (MPC) -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion -- References -- The Novel Electrocardiograph Sensor and Algorithm for Arrhythmia Computer Aided Detection -- 1 Introduction -- 2 Material and Methods -- 2.1 Proposed ECG Sensor -- 2.2 Pan-Tomkins Algorithm -- 2.3 P-QRS-T Detection -- 3 Experimental Results -- 4 Conclusion -- References -- Optimizing Sensor Subset Selection with Quantum Annealing: A Large-Scale Indoor Temperature Regulation Application -- 1 Introduction -- 2 SSSO Problem in Relation to Temperature Regulation -- 3 Quantum Motivation -- 4 Materials and Methods -- 4.1 Large-Scale Indoor Temperature Sensor Dataset -- 4.2 Our Implementation of the SSSO Problem -- 4.3 Experimental Setup -- 4.4 Hybrid Quantum Implementation Using D-Wave Quantum Annealer -- 5 Experimental Results -- 6 Conclusion -- References -- Smart IoT-Based Wearable Lower-Limb Rehabilitation Assistance System -- 1 Introduction -- 2 System Design -- 2.1 Hardware Design -- 2.2 Data Flow and Application Design -- 2.3 Lower-Limb Rehabilitation Activity State Classification Algorithm -- 3 Conclusion -- References -- Using Machine Learning of Sensor Data to Estimate the Production of Cutter Suction Dredgers -- 1 Introduction -- 2 Literature Review -- 2.1 Dredger Productivity Estimation -- 2.2 Dredging Productivity Estimation in Similar Areas -- 2.3 Soil Classification.
3 Research Setting and Methodology.
Record Nr. UNINA-9910842281903321
Choi Bong Jun  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part II
Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part II
Autore Choi Bong Jun
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (355 pages)
Altri autori (Persone) SinghDhananjay
TiwaryUma Shanker
ChungWan-Young
Collana Lecture Notes in Computer Science Series
ISBN 3-031-53830-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- AI and Big Data -- Automated Fashion Clothing Image Labeling System -- 1 Introduction -- 2 Related Research -- 3 Fashion Clothing Image Labeling System -- 3.1 Dataset Collection -- 3.2 Image Preprocessing -- 3.3 Yolo Training and Labeling Results -- 4 Conclusion -- References -- AI-Based Estimation from Images of Food Portion Size and Calories for Healthcare Systems -- 1 Introduction -- 2 Dataset of Uzbek Foods -- 3 Proposed Method -- 4 Experimental Results and Analysis -- 5 Limitation and Future Work -- 6 Conclusions -- References -- Blockchain Technology as a Defense Mechanism Against Data Tampering in Smart Vehicle Systems -- 1 Introduction -- 2 Background and Literature Review -- 3 Data Tampering in Smart Vehicle Systems -- 4 Blockchain Technology as a Solution in Smart Vehicle Systems -- 4.1 Technical Foundations of Blockchain in Smart Vehicle Systems -- 4.2 Practical Implementations and Prototypes -- 5 Conclusion -- References -- Classification of Weeds Using Neural Network Algorithms and Image Classifiers -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Classification Models Architectures and Algorithms -- 4 Results -- 5 Future Scope and Conclusion -- References -- Weed and Crop Detection in Rice Field Using R-CNN and Its Hybrid Models -- 1 Introduction -- 2 Related Work -- 3 Methods and Materials -- 3.1 Experimental Site and Image Acquisition -- 3.2 Data Pre-processing -- 4 Weed Detection Method -- 4.1 Regions with RCNN -- 4.2 Regions with RCNN-LSTM -- 4.3 Regions with RCNN-GRU -- 5 Results and Discussions -- 6 Conclusion -- References -- Deep Learning -- Spatial Attention Transformer Based Framework for Anomaly Classification in Image Sequences -- 1 Introduction -- 2 Related Study.
3 Proposed Framework -- 3.1 Spatial Attention Module (SAM) -- 3.2 Shifted Window Transformer (SWIN) -- 3.3 SST for Anomaly Detection -- 4 Experimental Results and Discussions -- 4.1 Datasets -- 4.2 Results and Discussions -- 5 Conclusions -- References -- Development of LSTM-Based Sentence Generation Model to Improve Recognition Performance of OCR System -- 1 Introduction -- 2 Related Works -- 3 LSTM-Based Sentence Generation Model -- 3.1 Training Dataset -- 3.2 Implemented LSTM Model -- 4 Experiments and Results -- 5 Conclusion -- References -- Satellite Imagery Super Resolution Using Classical and Deep Learning Algorithms -- 1 Introduction -- 2 Background -- 2.1 Image Resolution -- 2.2 Interpolation for Image Enhancement -- 2.3 DWT and Noise Removal Techniques -- 3 Deep Learning Based Architectures for Image Super Resolution -- 3.1 High Level Architecture -- 3.2 Enhanced Deep Residual Networks for Single Image Super-Resolution(EDSR) -- 3.3 Wide Activation for Efficient and Accurate Image Super-Resolution(WDSR) -- 3.4 Deep Alternating Network(DAN) -- 4 Evaluation Metrics -- 5 Comparisons and Challenges -- 6 Comparisons and Challenges -- References -- Traffic Sign Recognition by Image Preprocessing and Deep Learning -- 1 Introduction -- 2 Related Works -- 2.1 Traditional Approach -- 2.2 Deep Learning Based Methods -- 3 Our Methodology -- 3.1 Dark Channel Prior Based Image Dehazing -- 3.2 Improved Detection Model -- 3.3 Data Augmentation -- 4 Experiments and Analysis -- 4.1 Results -- 4.2 Experimental Analysis and Discussion -- 5 Conclusion -- References -- Convolutional Autoencoder for Vision-Based Human Activity Recognition -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Convolutional Autoencoder (Conv-AE) -- 3.2 Convolutional Neural Network (CNN) -- 3.3 Pre-processing -- 3.4 Feature Representation -- 3.5 Classification.
4 Experimental Results -- 4.1 Datasets -- 4.2 Results and Discussions -- 5 Conclusions and Future Scope -- References -- Deep Learning Approach for Enhanced Object Recognition and Assembly Guidance with Augmented Reality -- 1 Introduction -- 2 Methodology -- 2.1 Dataset Collection and Image Pre-processing -- 2.2 Step Detection -- 3 Results and Discussion -- 3.1 Prototype -- 3.2 SSD Performance -- 3.3 YOLOv7 Performance -- 3.4 User Testing -- 4 Conclusion -- References -- 3D Facial Reconstruction from a Single Image Using a Hybrid Model Based on 3DMM and Deep Learning -- 1 Introduction -- 2 Related Work -- 2.1 3DMM-Based Methods -- 2.2 Image-Based Methods -- 3 Methodology -- 3.1 3D Morphable Model -- 3.2 Camera Model -- 3.3 Illumination Model -- 3.4 Model Fitting -- 4 Results Analysis -- 5 Conclusion -- References -- Human Activity Recognition with a Time Distributed Deep Neural Network -- 1 Introduction -- 2 Related Works -- 3 The Proposed Method -- 3.1 Input Dataset -- 3.2 Data Pre-processing -- 3.3 Time Distributed Frame Conversion -- 3.4 Time Distributed CNN Layers -- 3.5 LSTM Layers -- 3.6 Training and Testing -- 3.7 Evaluation -- 4 Experimental Results and Discussion -- 4.1 UCI Sensor Dataset [2] Results -- 4.2 OPPORTUNITY Sensor Dataset Results -- 5 Conclusions -- References -- Intelligent Systems -- Artificial Neural Network to Estimate Deterministic Indices in Control Loop Performance Monitoring -- 1 Introduction -- 2 Background -- 2.1 Control Performance Monitoring -- 2.2 CPM Performance Indices -- 2.3 Machine Learning -- 2.4 Control-Loop Performance Assessment Whit Machine Learning -- 3 Methodology -- 4 Results -- 4.1 The Model with Machine Learning -- 5 Conclusions -- References -- Interference Mitigation in Multi-radar Environment Using LSTM-Based Recurrent Neural Network -- 1 Introduction.
2 Signal Model and Interference Effect Analysis -- 3 LSTM-RNN Architecture -- 4 Methodology, Results and Discussions -- 5 Conclusions -- References -- Centrifugal Pump Health Condition Identification Based on Novel Multi-filter Processed Scalograms and CNN -- 1 Introduction -- 2 Experimental Setup -- 3 Proposed Framework -- 4 Results and Performance Evaluation -- 5 Conclusion -- References -- A Closer Look at Attacks on Lightweight Cryptosystems: Threats and Countermeasures -- 1 Introduction -- 1.1 Lightweight Cryptography -- 2 Related Work -- 2.1 Side-Channel Analysis and Countermeasures: -- 2.2 Light Lightweight Cryptographic Algorithm Design: -- 3 Types of Attacks on Cryptosystems -- 3.1 Passive Attacks -- 3.2 Active Attacks -- 4 Cryptographic Attacks -- 4.1 Ciphertext Only Attacks (COA) -- 4.2 Known Plaintext Attack (KPA) -- 4.3 Dictionary Attack -- 4.4 Brute Force Attack (BFA) -- 4.5 Man in Middle Attack (MIM) -- 5 Countermeasures for Lightweight Encryption -- 5.1 Fault Injection Attacks and Protections: -- 5.2 Post-quantum Lightweight Cryptography: -- 5.3 Energy-Efficient Cryptography: -- 5.4 Machine Learning and Lightweight Cryptography: -- 6 Conclusion -- References -- A Prototype of IoT Medication Management System for Improved Adherence -- 1 Introduction -- 2 The Design Methodology of an Innovative Pharmaceutical IoT Medication Product -- 2.1 External Technology of the Product -- 2.2 Internal Technology of the Product -- 2.3 Mobile Application to Control the Product -- 3 Prototype Development of an Innovative Pharmaceutical -- 4 Final Discussion -- References -- Mobile Computing and Ubiquitous Interactions -- Navigating the Complexities of 60 GHz 5G Wireless Communication Systems: Challenges and Strategies -- 1 Introduction -- 2 Weaknesses of the 60 GHz Massive MIMO System -- 3 Proposed Algorithm -- 3.1 Channel Model of Sparse Multipath.
3.2 SAMP Algorithm -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- A Survey on Channel Estimation Technique Classifications and Various Algorithms -- 1 Introduction -- 2 Channel Estimation -- 2.1 Channel Estimation Classification -- 2.2 Channel Estimation Algorithms -- 3 Discussions and Future Research -- References -- Wearable-Based SLAM with Sensor Fusion in Firefighting Operations -- 1 Introduction -- 2 Method -- 2.1 System Overview -- 2.2 Map Points Calculation (MPC) -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion -- References -- The Novel Electrocardiograph Sensor and Algorithm for Arrhythmia Computer Aided Detection -- 1 Introduction -- 2 Material and Methods -- 2.1 Proposed ECG Sensor -- 2.2 Pan-Tomkins Algorithm -- 2.3 P-QRS-T Detection -- 3 Experimental Results -- 4 Conclusion -- References -- Optimizing Sensor Subset Selection with Quantum Annealing: A Large-Scale Indoor Temperature Regulation Application -- 1 Introduction -- 2 SSSO Problem in Relation to Temperature Regulation -- 3 Quantum Motivation -- 4 Materials and Methods -- 4.1 Large-Scale Indoor Temperature Sensor Dataset -- 4.2 Our Implementation of the SSSO Problem -- 4.3 Experimental Setup -- 4.4 Hybrid Quantum Implementation Using D-Wave Quantum Annealer -- 5 Experimental Results -- 6 Conclusion -- References -- Smart IoT-Based Wearable Lower-Limb Rehabilitation Assistance System -- 1 Introduction -- 2 System Design -- 2.1 Hardware Design -- 2.2 Data Flow and Application Design -- 2.3 Lower-Limb Rehabilitation Activity State Classification Algorithm -- 3 Conclusion -- References -- Using Machine Learning of Sensor Data to Estimate the Production of Cutter Suction Dredgers -- 1 Introduction -- 2 Literature Review -- 2.1 Dredger Productivity Estimation -- 2.2 Dredging Productivity Estimation in Similar Areas -- 2.3 Soil Classification.
3 Research Setting and Methodology.
Record Nr. UNISA-996587859903316
Choi Bong Jun  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part I
Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part I
Autore Choi Bong Jun
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (450 pages)
Altri autori (Persone) SinghDhananjay
TiwaryUma Shanker
ChungWan-Young
Collana Lecture Notes in Computer Science Series
ISBN 3-031-53827-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Natural Language and Dialogue Systems -- HGAN: Editable Visual Generation from Hindi Descriptions -- 1 Introduction -- 2 Background -- 2.1 Text-to-Image Generation -- 2.2 Attention -- 3 Material and Method -- 3.1 Architecture -- 3.2 Word-Focused Channel Attention -- 3.3 Editing Module -- 3.4 Objective Functions -- 3.5 Generator Objective -- 3.6 Discriminator Objective -- 4 Dataset -- 5 Implementation -- 6 Result -- 7 Component Analysis -- 8 Conclusion -- 9 Limitation and Future Work -- References -- Adopting Pre-trained Large Language Models for Regional Language Tasks: A Case Study -- 1 Introduction -- 2 Pre-trained Language Models -- 3 Preparation of Sentiment Analysis Dataset -- 4 Fine Tuning of Language Models -- 5 Related Work -- 6 Conclusion -- References -- Text Mining Based GPT Method for Analyzing Research Trends -- 1 Introduction -- 2 Related Research -- 2.1 Text Mining -- 3 Research Trend Analysis System Utilizing GPT Based on Text Mining -- 3.1 Keyword Extraction -- 3.2 Training GPT Models -- 3.3 Generate Sentences -- 4 Conclusion -- References -- Effect of Speech Entrainment in Human-Computer Conversation: A Review -- 1 Introduction -- 2 Fundamental Concept About Entrainment in Human-Human Conversation -- 3 Entrainment/Alignment Strategies Employed in Voice-Based Human-Machine Conversation and Their Impact on User Experience and Satisfaction -- 3.1 Acoustic-Prosodic Entrainment -- 3.2 Lexical Entrainment -- 3.3 Syntactic Alignment -- 4 Potential Benefits of Incorporating Entrainment in Voice-Based Human-Machine Conversation -- 4.1 Naturalness -- 4.2 Enhanced Trustworthiness -- 5 Summary and Future Prospect -- 5.1 Implementing Entrainment for Mechanomorphic Design -- 5.2 Manipulation of Temporal Aspects of the Machine to Provide Enhanced Turn-Taking.
5.3 Manipulation of Machine's Cues for Better Entrainment -- References -- HUCMD: Hindi Utterance Corpus for Mental Disorders -- 1 Introduction -- 2 Challenges -- 3 Related Work -- 4 Proposed Approach for HUCMD -- 4.1 Symptom Words -- 4.2 Intensity Words -- 4.3 Frequency Words -- 4.4 History Words -- 4.5 Actor Words -- 4.6 Trailer Words -- 4.7 Utterance Generation Algorithm -- 4.8 Generated Utterances -- 5 Dataset Validation -- 5.1 Bidirectional Long Short Term Memory (Bi-LSTM) -- 5.2 Convolution Neural Network -- 5.3 Network Architecture -- 5.4 Sampling Algorithm -- 5.5 Intent Detection -- 5.6 Slot Prediction -- 6 Conclusion -- References -- Classification of Cleft Lip and Palate Speech Using Fine-Tuned Transformer Pretrained Models -- 1 Introduction -- 2 Dataset -- 3 Methods -- 3.1 Wav2Vec2 -- 3.2 SEW -- 3.3 SEW-D -- 3.4 UniSpeechSat -- 3.5 HuBERT -- 3.6 DistilHuBERT -- 4 Experimentation and Results -- 5 Conclusion -- References -- Affective Computing and Human Factors -- Visual-Sensory Information Processing Using Multichannel EEG Signals -- 1 Introduction -- 2 Main Part -- 2.1 Significance of Analysis and Classification of EEG Signals -- 2.2 EEG Signal Processing Based on Brain Computer Interface -- 3 Conclusion -- References -- Vision Transformer-Based Emotion Detection in HCI for Enhanced Interaction -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Methodology -- 5 Evaluation Metrics -- 6 Experimental Results -- 7 Conclusion -- References -- GenEmo-Net: Generalizable Emotion Recognition Using Brain Functional Connections Based Neural Network -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Dataset Description -- 3.2 Data Preprocessing -- 3.3 Feature Extraction -- 3.4 Model Architecture -- 3.5 Model Evaluation -- 4 Results and Discussion -- 5 Conclusion -- References.
Ear-EEG Based-Driver Fatigue Detection System Augmented by Computer Vision -- 1 Introduction -- 2 Proposed System -- 2.1 Ear-EEG Embedded Device -- 2.2 Computer Vision-Based on Face Features -- 2.3 Experiment -- 2.4 Deep Learning Model -- 3 Results and Discussion -- 4 Conclusion -- References -- Cross Cultural Comparison of Emotional Functional Networks -- 1 Introduction -- 2 Methodology -- 2.1 Datasets -- 2.2 Complex Network Analysis of the Brain During Emotion -- 3 Results and Observations -- 4 Discussion -- References -- Emotion Recognition Using Phase-Locking-Value Based Functional Brain Connections Within-Hemisphere and Cross-Hemisphere -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Dataset Description -- 3.2 Data Preprocessing -- 3.3 Feature Extraction -- 3.4 Feature Selection -- 3.5 Classification -- 4 Results and Discussion -- 5 Conclusion -- References -- Context-Aware Facial Expression Recognition Using Deep Convolutional Neural Network Architecture -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Model Architectures -- 4 Experiments and Discussion -- 4.1 Benchmark Datasets: Emotic and CAER -- 4.2 Experimental Setup -- 5 Conclusions -- References -- Human Centred AI -- Exploring Multimodal Features to Understand Cultural Context for Spontaneous Humor Prediction -- 1 Introduction -- 2 Features and Model -- 2.1 Audio -- 2.2 Video -- 2.3 Text -- 2.4 Fusion -- 3 Experiments and Results -- 3.1 Experimental Setup -- 3.2 Dataset and Data Preparation -- 3.3 Hyperparameters -- 3.4 Results -- 3.5 Discussion -- 4 Conclusions and Future Work -- References -- Development of Pneumonia Patient Classification Model Using Fair Federated Learning -- 1 Introduction -- 2 Related Work -- 2.1 Federated Learning -- 2.2 DenseNet (Dense Convolutional Network) [18] -- 2.3 CheXNet [21] -- 2.4 Loss Function -- 2.5 IID, Non-IID Condition.
3 Improve Transparency -- 3.1 MINIMAR (MINImum Information for Medical AI Reporting): Reporting Standards for Artificial Intelligence in Health Care [26] -- 4 Method -- 4.1 Dataset -- 4.2 Data Pre-processing, Augmentation -- 4.3 FFLFCN (Fair Federated Learning Loss Function Chest X-ray Dense Convolutional Network) Model Construction -- 5 Results -- 6 Conclusion -- References -- Artificial Intelligence in Medicine: Enhancing Pneumonia Detection Using Wavelet Transform -- 1 Introduction -- 2 Related Works -- 3 Dataset Description/Methodology -- 4 Experiments and Results -- 5 Future Research Work -- 6 Conclusion -- References -- Maximizing Accuracy in AI-Driven Pattern Detection in Cardiac Care -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Pre-processing for Cardiac Data -- 3.3 Algorithm Utilized -- 4 Results -- 4.1 Model Building -- 4.2 Model Validation -- 5 Conclusion -- References -- Development of IMU Sensor-Based XGBoost Model for Patients with Elbow Joint Damage -- 1 Introduction -- 2 Development of IMU Sensor-Based XGBoost Model -- 3 Experiment and Results -- 4 Conclusion -- References -- Application of Daubechies Wavelets in Digital Processing of Biomedical Signals and Images -- 1 Introduction -- 2 Determining Daubechies Discrete Wavelet Transform Coefficients -- 3 Construction of One-Dimensional Wavelet Transforms -- 4 Identification of Wavelet Methods in Denoising in Tomographic Images -- 5 Conclusion -- References -- An Integrated System for Stroke Rehabilitation Exercise Assessment Using KINECT v2 and Machine Learning -- 1 Introduction -- 2 Materials and Methods -- 2.1 Used Device -- 2.2 Machine Learning Model Selection -- 2.3 KIMORE Dataset -- 3 Experimental Setup -- 3.1 Device Setup -- 3.2 Instructions and Guidelines -- 4 Results -- 5 Conclusion and Future Works -- References.
Gastric Ulcer Detection in Endoscopic Images Using MobileNetV3-Small -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 The Dataset -- 3.2 Preprocessing -- 3.3 Architecture and MobilenetV3-Small -- 3.4 Performance Metrics -- 4 Results -- 5 Conclusion -- References -- Exploring Quantum Machine Learning for Early Disease Detection: Perspectives, Challenges, and Opportunities -- 1 Introduction -- 2 Related Work -- 3 Quantum Machine Learning (QML) in Medical Applications -- 3.1 Quantum Software Platforms and Tools -- 3.2 Quantum Machine Learning Models -- 3.3 Quantum Computing Hardware -- 4 QML Algorithms -- 4.1 Quantum Neural Networks (QNN) -- 4.2 Quantum Boltzmann Machines -- 4.3 Quantum Support Vector Machines -- 5 Challenges for Medical Translation -- 5.1 Noise Tolerance and Mitigation -- 5.2 Problem-Aware Model Optimization -- 5.3 Workflow Integration Complexities -- 6 Final Discussion -- 7 Conclusions -- References -- Human-Robot Interaction and Intelligent Interfaces -- Subject-Independent Brain-Computer Interfaces: A Comparative Study of Attention Mechanism-Driven Deep Learning Models -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 Proposed Transformer Model Architecture -- 2.3 Model Selection -- 3 Results and Discussion -- 4 Conclusion -- References -- PPHR: A Personalized AI System for Proactive Robots -- 1 Introduction -- 2 System Architecture -- 2.1 Sensing -- 2.2 Learning -- 2.3 Interacting -- 3 Methodology -- 3.1 Reinforcement Learning -- 3.2 Personalization of Models -- 3.3 Federated Learning -- 3.4 Extensibility of Models -- 3.5 Activity State -- 4 Implementation -- 4.1 Model Structure -- 4.2 Data Collection -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Classifying Service Robots in Commercial Places Based on Communication: Design Elements by Level of Communication -- 1 Introduction.
2 Related Works.
Record Nr. UNISA-996587860303316
Choi Bong Jun  
Cham : , : Springer, , 2024
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