Deep ConvNet Image Classifier based on Residual Network architecture trained on Caltech 101 Object Dataset
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Updated
May 8, 2024 - Python
Deep ConvNet Image Classifier based on Residual Network architecture trained on Caltech 101 Object Dataset
Replication of DeCAF paper's experiments for transfer learning
CNN-based image classification
Imperial College London EE4-62 Machine Learning for Computer Vision Coursework 1
Image recognition on CIFAR 10, CIFAR 100, Caltech 101 and Caltech 256 datasets. With the implementation of WideResNet, InceptionV3 and DenseNet neural networks.
Reimplementation of "VAE with a VampPrior" by Jakub M. Tomczak et al., as part of the DD2434 Machine Learning, Advanced Course at KTH
Content-Based Image Retrieval Using CNN and Hash
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