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1-d-dhrn

1d-convolutional-variational-autoencoder

Convolutional Variational Autoencoder for classification and generation of time-series

add-gcn

ADD-GCN: Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition (ECCV 2020)

aegan

This model is for anomaly detection, use an autoencoder to keep the image's overall structure, then use the G of GAN to simulate the detail of the image.

attention-module

Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"

b-cnn

Sample code of B-CNN paper (https://arxiv.org/abs/1709.09890) written in Python3+.

cbam.pytorch

Non-official implement of Paper：CBAM: Convolutional Block Attention Module

circularkernel

Integrating Large Circular Kernels into CNNs through Neural Architecture Search

cnn-for-paderborn-bearing-dataset

in Python

cnn-lstm-bilstm-deepcnn-clstm-in-pytorch

In PyTorch Learing Neural Networks Likes CNN(Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) 、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM

convolutional_lstm_pytorch

Multi-layer convolutional LSTM with Pytorch

deeprft

The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'

denoise

detect-lstm-model

检测恶意 URL and Request (Bi-LSTM、Bi-LSTM + CNN、CNN + Bi-LSTM、CNN + Bi-LSTM + CNN)

difformer

The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fault_diognosis_dataset

fno

fs-canet

A Page Demo For FS-CANet：https://hit-thusz-rookiecj.github.io/FS-CANet/

gcn

Implementation of Graph Convolutional Networks in TensorFlow

gfnet

[NeurIPS 2021] Global Filter Networks for Image Classification

grlnet

hinet

hkg

keras_bearing_fault_diagnosis

machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接

memae-anomaly-detection

MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.

mimii_baseline

A baseline sample code of anomaly detection for MIMII Dataset

mirnet

Official repository for "Learning Enriched Features for Real Image Restoration and Enhancement" (ECCV 2020). SOTA results for image denoising, super-resolution, and image enhancement.

ml-gcn

PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.