Computer Vision

Transfer learning with pretrained VGG16 and ResNet architectures for medical image analysis, achieving 92% validation accuracy.

Real-time vision-based system for American Sign Language gesture recognition with optimized CNN architectures, achieving 95% classification accuracy.