Rajdeep Chatterjee , Ph.D.'s repositories
1DCNN-IRIS-PyTorch
1 Dimensional Convolutional Neural Network for Iris dataset classification
DeepFace_Tutorial
Deepface: a python package for emotion detection, gender, age, and race identification. It can also detect human faces using different popular computer vision techniques
Fashion-Recommender
A deep learning-based fashion recommendation model
Google-Colab-Helper
A brief Google Colab guide for running non-gpu python programs
C-in-Colab
Run C programs in Google Colab environment.
HRpro-repository
A comprehensive Python-based framework for the recruitment process automation
LSTM-IRIS-PyTorch
LSTM implementation on IRIS dataset classification using PyTorch
Video-Classification
Video Classification of the UCF50 - Action Recognition Dataset
Fuzzy-Discernibility-Matrix
Fuzzy Discernibility Matrix-based a novel feature selection technique
Background-Replacement-Mediapipe
An easy python code for replacing the background using mediapipe and cvzone packages
cnn-and-cifer10
Convolutional Neural Network implementation on CIFER10 dataset
Cosine-Diversity
Cosine Diversity
DNN-IRIS-PyTorch
Deep Neural Network with Batch normalization for tabulat datasets.
DNNFaceDetection-Colab-Example
Download the following pre-trained model for face detection. However, one can use own model or other pre-trained models to detect faces.
DSA-Sparse-Matrix2Triplet
Sparse Matrix to Triplet and various triplet operations. e.g., transpose, addition, and multiplication.
Gradient_Descent_Demo
Gradient Descent Tutorial
Graph-Networkx-101
Basic Graph operations such as BFS, DFS, Shortest Path Length etc.
Image2Text
Python code to extract text from a given image
Logistic-Regression-MNIST-PyTorch
Logistic Regression example on MNIST dataset
MaskRCNN-Kangaroo
Mask RCNN instance segmentation custom training on Kangaroo Dataset
Mix-Decision-Boundary
Hybrid Decision Boundary
Plant-Disease-detection-Multiplatform-app
Plant diseases Classification using Deep Learning
Python-UTube-Video-Downloader
A python youtube video downloading GUI
Random-Image-Generation-and-Classification
Random Matrices with 0s and 1s have been generated and ResNet50 deep learning model has been employed to classify the types
stacked-racifer10net
My own stacked CNN model architecture for CIFER10 data classification
YOLACT-plus-plus
YOLACT++ instance segmentation custom training