Vladimir Kiselev's starred repositories
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
face-recognition.js
Simple Node.js package for robust face detection and face recognition. JavaScript and TypeScript API.
node-facenet
Solve face verification, recognition and clustering problems: A TensorFlow backed FaceNet implementation for Node.js.
facenet-pytorch
Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models
face-api.js
JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
ear-recognition
Employing Fusion of Learned and Handcrafted Features for Unconstrained Ear Recognition
tfjs-models
Pretrained models for TensorFlow.js
MagicOnion
Unified Realtime/API framework for .NET platform and Unity.
mmap-object
Shared Memory Objects for Node
Shared-Memory-NodeJS-Demo-Server
With this repo you can create a simple server to write/read to/from shared memory through two dedicated APIs.
go-cshared-examples
Calling Go Functions from Other Languages using C Shared Libraries
system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.