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1. IDCBreastCancer_histopathologyImages_deepResidualLearning IDCBreastCancer_histopathologyImages_deepResidualLearning Public

   IDC prediction in breast cancer histopathology images using deep residual learning with an accuracy of 99.37% in a subset of images containing a total of 7,500 microscopic images.

   Jupyter Notebook 3 2

2. Pneumonia-diagnosis-using-deep-residual-learning-with-a-classification-accuracy-of-98.22 Pneumonia-diagnosis-using-deep-residual-learning-with-a-classification-accuracy-of-98.22 Public

   Classification between normal and pneumonia affected chest-X-ray images using deep residual learning along with separable convolutional network(CNN). This methodology involves efficient edge preser…

   Jupyter Notebook 3 3

3. RahulSkr/junctionPredictionFromGeneSequence RahulSkr/junctionPredictionFromGeneSequence Public

   Splice junction prediction from gene sequences using recurrent neural networks

   Python 2

4. RahulSkr/skinCarcinomaDetection RahulSkr/skinCarcinomaDetection Public

   A deep neural network developed following the residual learning and separable convolution paradigms to diagnose basal and squamous cell carcinoma using a subset of ISIC dataset.

   Python 1

5. Object_Classification_Deep_Residual_Seperable_CNN_with_VGG16 Object_Classification_Deep_Residual_Seperable_CNN_with_VGG16 Public

   Object_Classification_Deep_Residual_Seperable_CNN_with_VGG16

   Jupyter Notebook

6. Emotion-Recognition-from-speech-signals-over-the-TESS-dataset Emotion-Recognition-from-speech-signals-over-the-TESS-dataset Public

   Emotion Recognition using matlab (Machine Learning using SVM and Random Forest)

   1