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So You Think You Can Program An Elevator
The 3rd edition of course.fast.ai
The complete blood count (CBC) dataset contains a total of 360 blood smear images of red blood cells (RBCs), white blood cells (WBCs), and Platelets with annotations.
Machine learning approach of automatic identification and counting of blood cells (RBC, WBC, and Platelet) with KNN and IOU based verification.
BCCD (Blood Cell Count and Detection) Dataset is a small-scale dataset for blood cells detection.
RBC_count, WBC count, WBC classification, disease diagnosis
A Keras implementation of YOLOv3 (Tensorflow backend)
Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow
Smart India Hackathon 2k18 project for detecting plant disease based on images of plant leaves having disease
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
Capstone Project for Udacity Machine Learning Nanodegree
Capstone project for Udacity's Machine Learning Engineer Nanodegree
Indian paper currency detection using Image Processing
This is the source code related to the paper 'Going deeper into copy-move forgery detection: exploring image telltales via multi-scale analysis and voting processes'
Classifying movie posters using CNN to check if genre of a movie can be determined by just looking at a poster.
Convolutional Neural Net to classify movie genres from posters
Movie Genre Prediction using Recurrent Neural Networks containing LSTM units
Materials for "Logo Detection Using PyTorch" presented at PyCon Thailand 2018
The work I did under Dr. S.K. Pal in the 2016 winter break.
Algorithms published for Image forgery Identificatio in various papers published
A list of papers, codes and other interesting collections pertaining to image tampering detection and localization.
Distinguishing Between Natural and Computer-Generated Images Using Convolutional Neural Networks in Keras.
A model to detecd Image splicing forgeries based on the VGG16 pre-trained model