AI-Powered Sign Interpretation: Merging VGG16 and ResNet50 for Superior Accuracy

Sign language recognition (SLR) is important for helping people who are deaf or hard of hearing communicate with others. This work studies how two popular deep learning models, VGG16 and ResNet50, are used for tasks connected to SLR. We used the VGG16 and ResNet50 models, and we got very high accuracy rates of 99.92% and 9995% in correctly recognizing sign language gestures. Our research shows that these models work well at accurately recognizing hand movements and gestures, which helps people who use sign language communicate more easily. Our research uses advanced computer methods to help make SLR systems better. This offers great chances for better communication and making things easier for everyone.