Vladimir Kiselev's starred repositories
tensorflow-face-detection
A mobilenet SSD based face detector, powered by tensorflow object detection api, trained by WIDERFACE dataset.
opencv-object-detection
:camera: Object detection with OpenCV on Java. DNN, HaarCascade, Template Matching, Color Detection etc.
computer_vision
Computer vision models
face-detection
Face detection implementation with different methods and applications
windapsearch
Python script to enumerate users, groups and computers from a Windows domain through LDAP queries
Dagger-Hilt-Tutorial
An example project to demonstrate how to use the Dagger-Hilt in Android.
focalboard
Focalboard is an open source, self-hosted alternative to Trello, Notion, and Asana.
insightface
State-of-the-art 2D and 3D Face Analysis Project
Face-Recognition
Face Recognition using pre-trained model built-on Arcface was implemented on Pytorch.
arcface-tensorflowlite
ArcFace face recognition implementation in Tensorflow Lite.
deep-face-recognition
One-shot Learning and deep face recognition notebooks and workshop materials
Getting-Things-Done-with-Pytorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
node-canvas
Node canvas is a Cairo backed Canvas implementation for NodeJS.
sashuIya.github.io
My website
NTU_Dataset
Here we share the NTU datasets to all the researchers who are working on biometrics and forensics field.
PalmprintRecognition
Palmprint recognition with PCA, LDA, LBPH and FusionCode
DPrimeLearning
Discriminative Index Learning for Palmprint Recognition
Palmprint_Recognition
This project is mainly to complete the palmprint feature extraction and classification tasks. The data set contains 99 people's palm print pictures, in which 3 palm print pictures of each person are distributed in the training set, and the other 3 palm print pictures are distributed in the test set. In this project, I tried the traditional method use SIFT to extract features and KNN for classification which get accuracy of 97.31%, and also tried the convolutional neural network method such as ResNet which get accuracy of 83.16%. In addition, I also tried to use the Gaussian filter, Gabor filter, LBP, etc. to process the palmprint image and extract the texture from the palmprint image, but these methods have not improved the accuracy of palmprint recognition.
Palmprint-Segmentation
CNN-based Palmprint Segmentation