Yao et al., 2022 - Google Patents
Eye movement and visual target synchronization level detection using deep learningYao et al., 2022
- Document ID
- 8971238692899516509
- Author
- Yao L
- Park M
- Grag S
- Bai Q
- Publication year
- Publication venue
- Australasian Joint Conference on Artificial Intelligence
External Links
Snippet
In recent years, deep learning has been widely used in the eye-tracking area. Eye-tracking has been studied to diagnose neurological and psychological diseases early since it is a simple, non-invasive, and objective proxy measurement of cognitive function. This project …
- 238000001514 detection method 0 title abstract description 56
Classifications
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- 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
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- 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
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- 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
- G06K9/00597—Acquiring or recognising eyes, e.g. iris verification
-
- 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
- G06K9/00335—Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
-
- 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
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
-
- 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 |
|---|---|---|
| Zunino et al. | Video gesture analysis for autism spectrum disorder detection | |
| Pampouchidou et al. | Automatic assessment of depression based on visual cues: A systematic review | |
| Karg et al. | Recognition of affect based on gait patterns | |
| Ganesh et al. | Deep learning techniques for automated detection of autism spectrum disorder based on thermal imaging | |
| Mengi et al. | Artificial intelligence based techniques for the detection of socio-behavioral disorders: a systematic review | |
| Gilanie et al. | An Automated and Real-time Approach of Depression Detection from Facial Micro-expressions. | |
| Huang et al. | Facial expression guided diagnosis of Parkinson's disease via high-quality data augmentation | |
| Singh et al. | Detection of stress, anxiety and depression (SAD) in video surveillance using ResNet-101 | |
| Elbattah et al. | Applications of machine learning methods to assist the diagnosis of autism spectrum disorder | |
| Iddrisu et al. | Event camera-based eye motion analysis: A survey | |
| Dadiz et al. | Detecting depression in videos using uniformed local binary pattern on facial features | |
| Zadoo et al. | Automated Parkinson's Disease Detection: A Review of Techniques, Datasets, Modalities, and Open Challenges | |
| Çetintaş et al. | Detection of autism spectrum disorder from changing of pupil diameter using multi-modal feature fusion based hybrid CNN model | |
| Singh et al. | Prediction of pain intensity using multimedia data | |
| Liu et al. | Multimodal depression detection based on self-attention network with facial expression and pupil | |
| Cheekaty et al. | Enhanced multilevel autism classification for children using eye-tracking and hybrid CNN-RNN deep learning models | |
| Ben Slama et al. | DBN-DNN: discrimination and classification of VNG sequence using deep neural network framework in the EMD domain | |
| Evangeline et al. | Facial Emotion Recognition of Online Learners Using a Hybrid Deep Learning Model. | |
| Yao et al. | Eye movement and visual target synchronization level detection using deep learning | |
| Xu et al. | Application of ResLSTM in Hypomimia Video Detection for Parkinson's Disease | |
| Wang et al. | BTN: Neuroanatomical aligning between visual object tracking in deep neural network and smooth pursuit in brain | |
| Xu et al. | Automatic diagnosis of depression based on attention mechanism and feature pyramid model | |
| Rafee et al. | Eye-movement analysis and prediction using deep learning techniques and Kalman filter | |
| Oliveira et al. | Facial Expression Analysis in Parkinsons’s Disease Using Machine Learning: A Review | |
| Lee et al. | Mild cognitive impairment prediction based on multi-stream convolutional neural networks |