Table Detection and Extraction Using Deep Learning ( It is built in Python, using Luminoth, TensorFlow<2.0 and Sonnet.)

Symbol detection in online handwritten graphics using Faster R-CNN

Scaling Object Detection by Transferring Classification Weights

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

Wildfire smoke detection with Faster R-CNN via Pytorch 🔥🚒🧑‍🚒

Tensorflow Faster R-CNN for Windows and Python 3.5

Region Proposal Network (RPN) of Faster R-CNN implementation in Python and Tensorflow 1.8 with explanations.

Faster R-CNN for ncnn framework

Automatic detection of bike-riders who are not wearing helmets. Faster-RCNN model is trained by supervised learning using TensorFlow API which detects the objects and draws the bounding box with prediction score.

Convolutional Neural Networks repository for all projects of Course 4 of 5 of the Deep Learning Specialization covering CNNs and classical architectures like LeNet-5, AlexNet, GoogleNet Inception Network, VGG-16, ResNet, 1x1 Convos, OverFeat, R-CNN, Fast R-CNN, Faster R-CNN, YOLO, YOLO9000, DeepFace, FaceNet and Neural Style Transfer.

This is a face mask detection project implemented with the Pytorch. We use End-to-End Object Detection with Transformers model (DETR) and Face Mask Detection dataset available on kaggle.

Due to the COVID-19 regulation, people have to wear masks to protect themselves. Also, you need to create a system to find out if a person is wearing a mask or not. Also, this system should give a warning or sound when people are not wearing masks. So, I created the model with the help of Fast-R-CNN

Source code to our paper "On the use of a cascaded convolutional neural network for three-dimensional flow measurements using astigmatic PTV"

Face_Emotion_Recognition___Object_Detection__With OpenCV tensorflow, pytorch, fasterRCNN, MTCNN

This repository is dedicated to the task of object detection specifically for detecting human heads. The project focuses on developing and implementing algorithms and models that can accurately detect and localize human heads within images or video frames.

Detection of persons in a video