Net Engine FPGA with Software is an FPGA accelerator that enhances CNN performance in embedded systems by offloading tasks like 2D convolution and max-pooling, featuring the complete design of the Net Engine IP, software drivers, pre-trained models, and test data for facial computing.

American Sign Language (ASL) Detection using CNN

Denoising Diffusion Medical Model (DDMM) on PyTorch for generating datasets of Acute Lymphoblastic Leukemia 🩺💜

Facial Emotion detection involves analysis of images or videos of faces to identify emotions based on the facial expressions

AI model from scratch in C++ for image classification (MNIST dataset)

Focused on advancing credit card fraud detection, this project employs machine learning algorithms, including neural networks and decision trees, to enhance fraud prevention in the banking sector. It serves as the final project for a Data Science course at the University of Ottawa in 2023.

Verilog Codes for various Design

Project for lecture 5 Neural Networks to "Artificial Intelligence with Python" Harvard course

This project utilizes a CNN model to classify cat and dog images through training and testing processes. The model is created using the Keras library on the TensorFlow backend.

NLP-FinHeadlines-MoodTracker is a NLP project utilising sentiment analysis on financial news headlines. It employs a combination of CNN and LSTM layers to predict sentiment (positive, negative, neutral). The model incorporates an embedding layer, 1D convolution, max pooling, bidirectional LSTM, dropout, and dense layer for sentiment classification.

Building a HTTP-accessed convolutional neural network model using TensorFlow NN (tf.nn), CIFAR10 dataset, Python and Flask.

A beginner-level implementation of the Convolutional Neural Network or CNN, which is an essential algorithm in image processing.

A CNN Architecture classifies 14 kinds of automobile parts.

Machine Learning For Beginners - Image Classification Model Deployment

Machine Learning For Beginners - Rock, Paper, dan Scissors Image Classification

Ensemble Classifier

Deep Convolutional Encoder-Decoder Architecture implemented along with max-pooling indices for pixel-wise semantic segmentation using CamVid dataset.

Deep learning using CNN in tensorflow on Kaggle image dataset containing 87,900 different healthy and unhealthy crop leaves spanning 38 unique classes.