Lv et al., 2022 - Google Patents
Deep learning for intelligent human–computer interactionLv et al., 2022
View HTML- Document ID
- 8175067752536211472
- Author
- Lv Z
- Poiesi F
- Dong Q
- Lloret J
- Song H
- Publication year
- Publication venue
- Applied Sciences
External Links
Snippet
In recent years, gesture recognition and speech recognition, as important input methods in Human–Computer Interaction (HCI), have been widely used in the field of virtual reality. In particular, with the rapid development of deep learning, artificial intelligence, and other …
- 230000003993 interaction 0 title abstract description 143
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Health care, e.g. hospitals; Social work
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/01—Social networking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2203/00—Indexing scheme relating to G06F3/00 - G06F3/048
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Lv et al. | Deep learning for intelligent human–computer interaction | |
Sapiński et al. | Emotion recognition from skeletal movements | |
Hakim et al. | Dynamic hand gesture recognition using 3DCNN and LSTM with FSM context-aware model | |
Papastratis et al. | Continuous sign language recognition through a context-aware generative adversarial network | |
Papadopoulos et al. | Interactions in augmented and mixed reality: an overview | |
Hussain et al. | A multimodal deep log-based user experience (UX) platform for UX evaluation | |
Šumak et al. | Sensors and artificial intelligence methods and algorithms for human–computer intelligent interaction: A systematic mapping study | |
Luqman et al. | Towards hybrid multimodal manual and non-manual Arabic sign language recognition: MArSL database and pilot study | |
Kansizoglou et al. | Continuous emotion recognition for long-term behavior modeling through recurrent neural networks | |
Ma et al. | Traffic command gesture recognition for virtual urban scenes based on a spatiotemporal convolution neural network | |
Chang et al. | Multi-modal residual perceptron network for audio–video emotion recognition | |
Kraljević et al. | A dynamic gesture recognition interface for smart home control based on croatian sign language | |
Podder et al. | Signer-independent Arabic Sign Language recognition system using deep learning model | |
Paravati et al. | Human-computer interaction in smart environments | |
Xia et al. | A sign language recognition system applied to deaf-mute medical consultation | |
Kapuscinski et al. | Recognition of signed expressions in an experimental system supporting deaf clients in the city office | |
Amangeldy et al. | Sign language recognition method based on palm definition model and multiple classification | |
Fu et al. | Emotion recognition in conversations: A survey focusing on context, speaker dependencies, and fusion methods | |
Xiang et al. | Multimodal fusion of voice and gesture data for UAV control | |
Thao et al. | Attendaffectnet–emotion prediction of movie viewers using multimodal fusion with self-attention | |
Razzaq et al. | A hybrid multimodal emotion recognition framework for UX evaluation using generalized mixture functions | |
Abdul Ameer et al. | Empowering communication: a deep learning framework for Arabic sign language recognition with an attention mechanism | |
González-Rodríguez et al. | Towards a Bidirectional Mexican Sign Language–Spanish Translation System: A Deep Learning Approach | |
Pereira et al. | Systematic Review of Emotion Detection with Computer Vision and Deep Learning | |
Liang et al. | Mmateric: Multi-task learning and multi-fusion for audiotext emotion recognition in conversation |