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Welcome to the Intelligent Computer Vision Lab
Welcome to the Intelligent Computer Vision Lab
Research Interest of ICV Lab
Deep Learning and Machine Learning
Medical 2D/3D Image Analysis using PET/CT
Gaze Estimation and Driver Behavior Classification
Biometric System (Ocular Region Segmentation)
Image Enhancement and Semantic Segmentation
More About ICV Lab
Study of segmentation using Sclera-Net on the SBVPI database
Study of the correct sclera segmentation results using Sclera-Net on the UBIRIS.v2 database
Dual-task hierarchical architecture for Polyp and Surgical Instrument Segmentation
Dual-task hierarchical architecture for Polyp and Surgical Instrument Segmentation
HFRF-Net for Surgical and Polyp Segmentation
Overview of the Proposed Methodology
HFRF Network Architecture
Efficient Feature-Preserving Segmentation Network of Retinal Images
Efficient Feature-Preserving Segmentation Network of Retinal Images
Proposed EFPS-Net Framework for Optic Cup and Optic Disc Segmentation.
Applications of Proposed Methodology
EFPS Network Architecture
Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor
Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor
CNN-based driver’s gaze classification procedure without PCCR vector (scheme 1).
Experimental environment and proposed gaze detection system in vehicle environment
Gaze zones in our experiments
News & Highlights
News & Highlights
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