junyu1 Goto Github PK

12306

12306智能刷票，订票

bisru

bitcoin

Bitcoin Core integration/staging tree

clustering-with-deep-learning

Generic implementation for clustering with deep learning : representation learning (DNN) + clustering

cpac

Pytorch implementation of our article "Clustering-driven Deep Embedding with Pairwise Constraints"

deep-k-means-pytorch

Code for ICML 2018 paper 'Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions'

deep-residual-shrinkage-networks

The deep residual shrinkage network is a variant of deep residual networks.

deeptraffic

Deep Learning models for network traffic classification

dgfraud-tf2

A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X

dl-4-tsc

Deep Learning for Time Series Classification

eos

An open source smart contract platform

facenet

Face recognition using Tensorflow

facenet-pytorch-vggface2

A PyTorch implementation of the 'FaceNet' paper for training a facial recognition model with Triplet Loss using the VGGFace2 dataset. A pre-trained model using Triplet Loss is available for download.

facerecognition

Face recognition using triplet loss, implementing FaceNet with pytorch.人脸识别项目，提供一个小型数据集用作验证，使用三元组损失函数(Triplet loss)提升准确率和泛化能力，对FaceNet进行了一种实现。

fs-net

Code for “FS-Net: A Flow Sequence Network For Encrypted Traffic Classification”

fs-net-1

FS-Net: A Flow Sequence Network For Encrypted Traffic Classification

google-research

Google Research

iic

Invariant Information Clustering for Unsupervised Image Classification and Segmentation

image-classification

Image Classification using SIFT, Bag of words, k means clustering and SVM Classification

junyu1.github.io

junyu1.github.io-cart

keras-quadruplet-loss

for APTOS 2019 Blindness Detection

keras-triplet-loss-mnist

Keras model trained using semi-hard triplet Loss (tensorflow function) on MNIST

maltrail

Malicious traffic detection system

mampf

Code for “MaMPF: Encrypted Traffic Classification Based on Multi-Attribute Markov Probability Fingerprints”

metric-learning-divide-and-conquer

Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019

models

Models and examples built with TensorFlow

mxnet-batch_hard_triplet_loss

mxnet version batch hard triplet loss

plutowo

plutoyo