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In this project we use a Lightweight-CNN based model to classify instruments from the Freesound audio data set. We make use of Mel-Spectrogram features from the input audio data as the input to the CNN model. To add robustness to the model, we use a novel data augmentation technique based on the Cut-Mix algorithm.
Implementation of CutMix Augmentation with Keras.
Through this project we will try to understand CutMix by implementing it on a simple problem of cat-vs-dog classification.
Python codes to implement DeMix, a DETR assisted CutMix method for image data augmentation
This repository contains the code and the report for the coursework of INFR11031 Advanced Vision, a postgraduate course offered at The University of Edinburgh. The task was to train on limited and improve the accuracy of the ResNet-50 classifier on a small subset of the ImageNet dataset containing 50K training images and 50K test images. Achieved a mark of 74%