TANG16's repositories
Transfer-Learning-in-keras---custom-data
Implementing Transfer Learning for custom data using VGG-16 and Resnet-50
MGTN
2021 AAAI Modular Graph Transformer Networks for Multi-Label Image Classification; Official GitHub: https://github.com/ReML-AI/MGTN
LM-MLC
Label Mask for Multi-label Classification
C-Tran
General Multi-label Image Classification with Transformers
vision
Datasets, Transforms and Models specific to Computer Vision
multimodal-label-distribution-learning
Multimodal label distribution learning
LaMP
ECML 2019: Graph Neural Networks for Multi-Label Classification
Heart_Attack_Prediction-Using_Feature-Selection_Algorithm
Heart Attack Prediction by implementing Feature Selection such as SelectKBest & Recursive Feature Elimination
l0bnb
Solves the best subset selection problem
mutual-information-feature-selection
Use mutual information to select features in a Titanic data set
DistributedFeatureSelection
This is the COMP4450 group research project for our team in semester 1 2021 at the ANU. Our goal is to try to perform feature selection on large datasets to cope with the "curse of dimensionality" problem.
feature-selection-with-the-highest-accuracy
Feature selection considering the composition of feature relevancy based on information theory
Multitask-Emotion-Recognition-with-Incomplete-Labels
This is the repository containing the solution for FG-2020 ABAW Competition
tensorflow-cnn-finetune
Finetuning AlexNet, VGGNet and ResNet with TensorFlow
cv_template
一个图像复原或分割的统一框架，可以用于去雾🌫、去雨🌧、去模糊、夜景🌃复原、超分辨率👾、像素级分割等等。
TensorFlow_Engineering_Implementation
The source code and dataset about <Deep Learning - Best Practices on TensorFlow Engineering Implementation>
feature-selection-extraction
Feature selection and feature extraction code implementation from the paper Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review. Link -> https://arxiv.org/abs/1905.02845
Ego-network_Embedding
Global and Local Feature Learning for Ego-Network Analysis
TensorFlow2.0_ResNet
A ResNet(ResNet18, ResNet34, ResNet50, ResNet101, ResNet152) implementation using TensorFlow-2.0.
classic-convolution-network
里面会保存许多优秀的卷积神经网络结构，这些结构可以帮助我们更好的设计网络。