A simple python module to generate anchor (aka default/prior) boxes for object detection tasks.

A real time soda can object detector using TensorFlow's Regions with Convolutional Neural Networks (R-CNN) adaptation integrated into Django web framework.

ORCA: Oceanic Recognition & Classification Application for sea-life analysis systems.

Mask R-CNN creates a high-quality segmentation mask in addition to the Faster R-CNN network. In addition to class labels and scores, a segmentation mask is created for the objects detected by this neural network. In this repository, using Anaconda prompt step by step Mask R-CNN setup is shown.

A collection of computer vision projects, specifically covering image classification and object detection.

These days we all are using mask just because of Covid 19. So i build this website to detect whether your image is using mask or not by using Computer Vision and Deep Learning Algorithm to detect the image.

In this repository is my experimental thesis work on the recognition of museum works through object detection techniques.

System for detecting product defects from the production line based on digital image processing using neural networks

Object detection using R-CNN model from scratch.

An object detection project implemented using Transfer Learning and R-CNN model. The object considered for this project is a "cellphone"

Useful code for the users of the food flipping dataset, published in Nature Scientific Data.

An IoT-based safety system utilising deep learning techniques to analyse environmental sounds in real-time. Employed sensors to capture audio signals and leveraged classification algorithms, including CNN-based and RNN-based models, for accurate sound recognition.

Implementation of Libra R-CNN: Towards Balanced Learning for Object Detection

Modifying pre-trained torchvision models.

Detecting Laryngeal Cancer from CT SCAN images using Improvised Deep Learning based Mask R-CNN Model

RCNN based Model Training

This project is centered around leveraging CRNN (Convolution Recurrent Neural Networks) and Digital Image Processing principles to extract license plates from car images and convert them to text. By using advanced AI algorithms and computer vision techniques, the project aims to provide a reliable and accurate way to recognize license plates.

Repo containing computer vision object detection work to locate bacterial flagellar motors from 2D cryogenic electromagnetic images.

Tensorflow-based framework which lists attentive implementation of the conventional neural network models (CNN, RNN-based), applicable for Relation Extraction classification tasks as well as API for custom model implementation

In this assignment I have to build a Mask R-CNN based keypoint detector model using Detectron2. Detectron2 was written in PyTorch and contains many state-of-the-art obejct detection models with pretrained weights.