Sahil Rajesh Dhayalkar's repositories
TensorFlow_Speech_Recognition_Challenge
Implemented 3 neural network architectures: 1) Combination of RNN LSTM nodes and CNN, 2) CNN with residual blocks similar to ResNet, 3) Deep RNN LSTM network; and compared their performance to detect 12 speech commands.
Invasive_Species_Monitoring
Implemented convolutional neural network GoogLeNet with Inception modules and Ensemble of Inception V3, Xception, ResNet50 using transfer learning to detect invasive hydrangea in Brazilian national forest images dataset from Kaggle. Programmed in Keras using TensorFlow backend.
Large_Scale_GeoVisual_Search
Image visual similarity based search in NAIP satellite imagery of some areas of California using Deep Learning. Deep CNN provides output features that are converted into 512-bit binary vector that compactly represents the input image and can be used for similarity based search.
Distracted_Driver_Detection
GoogLeNet architecture with Inception modules that can detect the driver's activity or distraction which can be used to aid autonomous driving agent about driver's state.
Facial_Emotion_Recognition
Convolutional neural network model similar to VGG-D that can detect emotions given facial images. Achieved an accuracy of 65% on the FER-2013 dataset. Code in Keras
Grayscale_to_Color_using_CNN
Convolutional Neural Network architecture to generate Color images from Grayscale input images. Specifically, it generates color images in the YUV channels space when given input grayscale images in the Y channel.
BinaryNet-on-tensorflow
binary weight neural network implementation on tensorflow
generative-models
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
MNIST_Digit_Recognizer_Kaggle
Test Accuracy: 99.4%. Kaggle Rank: Top 13%. Convolutional neural network using TensorFlow to correctly identify digits from handwritten images
python-geospatial-analysis-cookbook
Over 60 recipes to work with topology, overlays and indoor routing
resnet-imagenet-caffe
train resnet on imagenet from scratch with caffe
tensorflow
Computation using data flow graphs for scalable machine learning