conv2d

Official code for ResUNetplusplus for medical image segmentation (TensorFlow & Pytorch implementation)

Basic Gesture Recognition Using mmWave Sensor - TI AWR1642

Benchmarks across Deep Learning Frameworks in Julia and Python

2D Convolutional Recurrent Neural Networks implemented in PyTorch

Numpy implementation of deep learning

layers

Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images

This code uses the pyTorch Conv2D modules to make the PIV algorithms work faster on GPU

Mokka is a minimal Inference Engine for Dense and Convolutional 2D Layer Neural Networks. Written on a single C++ header, it uses AVX2

A project to perform people identification at a distance using face and gait data with deep learning

A project to perform people identification at a distance using face and gait data with deep learning

A deep learning project implementing a Convolutional Neural Network (CNN) to classify images of cats and dogs. Built using TensorFlow/Keras, this project demonstrates fundamental computer vision techniques including data preprocessing, augmentation, and model training.

This project implements a Convolutional Neural Network (CNN) using the PyTorch framework to classify handwritten digits from the famous MNIST dataset (provided via the Kaggle Digit Recognizer competition).

A FAST pure numpy based 1D, 2D, even n-dimensional convolution library.

In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset.

This PyTorch-based project implements a deep neural network for multi-class classification of fashion items. The dataset consists of images categorized into three classes: glasses vs. sunglasses, shoes, and trousers vs. jeans.

Convolutional Neural Network to Classify Dogs and Cat. I built a ImageClassifier which classifies and tells you whether its a Dog image or a Cat image. I built a convolutional network which consists of Three Convolution layer and Three MaxPooling layer. Each Convolutional layer has filters, kernel size. Maxpooling layer has stride and pooling si…

Keras Convolutianl Networks

IMAGE CLASSIFICATION USING CNN and MobileNetV3

Creating a classifier for the German Traffic Signs dataset that classifies images of traffic signs into 43 classes.