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Autore: | Choi Bong Jun |
Titolo: | Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part I |
Pubblicazione: | Cham : , : Springer, , 2024 |
©2024 | |
Edizione: | 1st ed. |
Descrizione fisica: | 1 online resource (450 pages) |
Altri autori: | SinghDhananjay TiwaryUma Shanker ChungWan-Young |
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. | |
Titolo autorizzato: | Intelligent Human Computer Interaction |
ISBN: | 3-031-53827-7 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996587860303316 |
Lo trovi qui: | Univ. di Salerno |
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