Python library to fetch image urls based on keywords and download from Bing.com.

PyTorch implementation of "Dynamic Structure Pruning for Compressing CNNs" (AAAI 2023 Oral)

CNN Image classification of trash of 6 categories in tensorflow and pytorch

Image Classification on CIFAR-10 using Theano

learning data science including languages Python and SQL, data visualisation and machine learning

Using CNN for classifying dogs and cats images

Deep Learning - Portability and optimization of a neural network for rapid damage detection in earthquakes using OpenVINO toolkit

The purpose of this project was to simply test a CNN model on a competition FER2013 dataset.

Finetuned pretrained-CNN architectures on Kaggle's FGVC21 plant pathology dataset (Implemented in Keras)

Explores the use of a simple CNN model for the detection of COVID-19 in X-ray images. Leveraging a dataset from Kaggle, the pipeline includes preprocessing, model architecture design, performance evaluation, and testing on new cases.

This project consists of following steps: - dataset creation with web scraping (BeautifulSoup) - data pre-processing (DifPy, Rembg, Keras) - CNN deep learning model training (used MobileNet V2 model) and training (Tensorflow) - testing the model and analyzing the results.

The project includes a detailed explanation of the CNN and ICP algorithms, along with their implementation in Python using popular deep learning and computer vision libraries such as TensorFlow, Keras, and OpenCV. The dataset used for training and testing the models is the CIFAR-10 dataset, which consists of 60,000 32x32 color images in 10 classes.

Android app that identifies UT and UTD landmarks

Build end-to-end DL pipeline for computer vision (Image classification) for “Chest Disease Classification from Chest CT Scan Images” and deploy Flask web app to AWS EC2 with Docker and CI/CD tool: Jenkins