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1. Lipreading-Using-Mutimodal-Speech-Recognition Lipreading-Using-Mutimodal-Speech-Recognition Public

   Multimodal Speech Recognition for phoneme level prediction using Audio-Visual data from TCDTIMIT dataset implementing RNNs with LSTMs for the audio subnetwork and CNN-LSTMs for the video subnetwork.

   Python 15 8

2. nemo_asr_app nemo_asr_app Public

   Spanish_ASR

   Jupyter Notebook 4

3. Studying-the-Robustness-of-GANs-on-Noisy-Data-using-MNIST-and-EMNIST-Datasets Studying-the-Robustness-of-GANs-on-Noisy-Data-using-MNIST-and-EMNIST-Datasets Public

   Pytorch implementation of GANs on MNIST dataset and testing the robustness of the GANs by incorporating Gaussian Noise and EMNIST dataset.

   Jupyter Notebook

4. VQA-System VQA-System Public

   Visual Question Answering: given an image and a question related to the image in natural language, the systems answer the question in natural language from the image scene.

   Python

5. Autoencoder-on-MNIST-in-Pytorch Autoencoder-on-MNIST-in-Pytorch Public

   The Autoencoder contains an encoder and decoder where encoder stores the images input in a compressed form and decoder retrieves back the Images.

   Python 6 7

6. Interpretable-FeedForward-CNNs Interpretable-FeedForward-CNNs Public

   Interpretable Feedforward Convolutional Neural Networks: Implemented using Saab transform in cascade with Least Square Regressor for constructing the layers. Test on MNIST Handwritten digit dataset.

   Python 1 1