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Designed and Developed end-to-end scalable Deep Learning Project. It is a detection system trained using InceptionV3(CNN model) + GRU(Sequential model) model to classify a video as Real or Fake. Obtained the test accuracy of 89%.
Endoscopy Image Processing & Classification. Academic project as a part of the course AI in Biomedicine. Classify using pre-trained InceptionNetv3 and EfficientNetB2 classifiers and compare the accuracy.
The goal of the project is to improve a kaggle project about Dog Breed Classification, achieving an higher test accuracy. The original project achieved 79% of accuracy on the test set, while this one goes up to 87%. Also further improvements were made to the data processing pipeline in terms of modularity and performance.