A VGG practical on convolutional neural networks

A command line version of https://github.com/rykov8/ssd_keras

The repo contains all my codes for Data Analysis on MNIST dataset. The algorithms used were as follows: Random Forest, SVM, KNN, Convolution Neural Nets.

UI to rapidly tag images

Classify Traffic Signs.

My solution to stanford cs231n: CNN for visual recognition

CS231n: Convolutional Neural Networks for Visual Recognition Assignments Implementation

My solutions to CS231N (Convolutional Neural Networks for Visual Recognition, Spring 2017)

visual search microservices for go game sgf files .

Implementing autonomous capabilities with a convolutional neural network (CNN) and machine vision on a modified RC car, using a Raspberry Pi and an Arduino, written in Python and C, and utilising the TensorFlow and OpenCV libraries

Implement SS-CNN "Dubey et al. Deep Learning the City ECCV16"

The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datase…

Semantic neural network to realize pixel-wise classification of 2D nano-material using Matlab

The repository implements the a simple Convolutional Neural Network (CNN) from scratch for image classification. I experimented with it on MNIST digits and COIL object dataset.

Deep CNN classification implementation trained with MNIST data set

Used Convolutional Deep Neural nets to extract features from the image

Sign Language Detection Using CNN