Biography
Shams Rehman is a Senior Lecturer in the Department of Computer Science at HITEC University Taxila and the Director of the International Computer Vision Research Laboratory (ICVRL).
With extensive academic experience in Artificial Intelligence and Visual Computing, his research interests encompass Computer Vision, Deep Learning, Medical Image Analysis (including early drowning detection, COVID-19 screening, and breast cancer classification), Human Action & Gait Recognition, and Remote Sensing Land Scene Classification.
He actively mentors undergraduate and graduate research scholars and collaborates on global AI research initiatives.
Research Interests
Education
Publications (11)
A Deep Learning Approach to Early Drowning Detection for Child Safety using ResNet and Flower Pollination Algorithm
IEEE Transactions / Applied Computer Vision, 2026
Modelling of Innovative Approaches for Drowning Prevention: Customized CNNs and Optimization of Binary Chimps for Early Detection
Springer Visual Computing Journal, 2026
Deep Attention-Guided Network for Medical Image Segmentation
IEEE Transactions on Medical Imaging, 2025
Real-Time Object Detection in Aerial Imagery Using Lightweight Transformers
Computer Vision and Pattern Recognition (CVPR), 2025
A Comprehensive Survey of Vision Transformers in Medical Imaging
ACM Computing Surveys, 2025
Efficient Panoptic Segmentation for Autonomous Driving Scenes
International Conference on Computer Vision (ICCV), 2025
Deep Neural Networks for Medical Image Classification: Automated Breast Cancer and COVID-19 Diagnosis
IEEE Journal of Biomedical and Health Informatics, 2025
GAN-Based Synthetic Data Augmentation for Rare Disease Classification
Medical Image Analysis, 2024
Robust Face Recognition Under Occlusion Using Part-Based Feature Fusion
Pattern Recognition, 2024
Multi-Spectral Satellite Image Classification Using Hybrid CNN-Transformer Architecture
Remote Sensing of Environment, 2024
Temporal Action Detection in Surveillance Videos Using Graph Neural Networks
European Conference on Computer Vision (ECCV), 2024
Projects
MedSeg-AI: Intelligent Medical Image Segmentation Platform
ActiveAn AI-powered platform for automated segmentation of medical images including CT, MRI, and X-ray scans with clinical-grade accuracy.
TerraVision: Satellite Image Analysis for Environmental Monitoring
ActiveDeep learning-based satellite image analysis platform for land use classification and environmental change detection.
ActionNet: Video Understanding for Smart Surveillance
ActiveIntelligent video analytics system for automated activity detection and anomaly recognition in surveillance footage.
SynMed: Synthetic Medical Data Generation Framework
CompletedA GAN-based framework for generating high-fidelity synthetic medical images to address data scarcity in healthcare AI.