oral_cancer_detection
COVID-19 CT scan image classification using EfficientNetB2 with transfer learning and deployment using Streamlit. This project focuses on accurately classifying CT scan images into three categories: COVID-19, Healthy, and Others. Leveraging transfer learning on pretrained EfficientNetB2 models, the classification model achieves robust performance.
This project uses the VGG16 and EfficientNetB2 models to recognize facial emotions in the FER-2013 dataset, classifying expressions into seven emotions.
Music emotions and themes classifier app could recognize 56 classes using three trained models (based on ResNet50, InceptionNetV2, EfficientNetB3), applying the transfer learning approach.
Implementation of Deep Learning Techniques in endoscopic images using Deep Learning
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