panbo-bridge

pdf

编程电子书，电子书，编程书籍，包括C，C#，Docker，Elasticsearch，Git，Hadoop，HeadFirst，Java，Javascript，jvm，Kafka，Linux，Maven，MongoDB，MyBatis，MySQL，Netty，Nginx，Python，RabbitMQ，Redis，Scala，Solr，Spark，Spring，SpringBoot，SpringCloud，TCPIP，Tomcat，Zookeeper，人工智能，大数据类，并发编程，数据库类，数据挖掘，新面试题，架构设计，算法系列，计算机类，设计模式，软件测试，重构优化，等更多分类

competition

Comprehensive-analysis-of-Deep-learning-for-electroencephalogram-EEG-classification-tasks

EEG emotion classification using CNN

image_processing_for_mold_damage_detection

Machine Learning and OpenCV based approaches for detecting surface defects in casting products

eeg-emotion-recognition-base-gan-and-cnn

sts_transformer

BackgroundMattingV2

Real-Time High-Resolution Background Matting

Chinese-Text-Classification-Pytorch

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

DBPN-Pytorch

The project is an official implement of our CVPR2018 paper "Deep Back-Projection Networks for Super-Resolution" (Winner of NTIRE2018 and PIRM2018)

Deep-Residual-Shrinkage-Networks

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

DeepLearningSlideCaptcha

Deep Learning Slide Captcha

DRN

Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

ECE-C247-EEG-GAN

GAN and VAE implementations to generate artificial EEG data to improve motor imagery classification. Data based on BCI Competition IV, datasets 2a. Final project for UCLA's EE C247: Neural Networks and Deep Learning course.

EEG-Emotion-Recognition

This is a final project for my 2019 Winter course "Pattern Recognition".

EmoRecogKeras

This repository is a part of EEG-Emotion Recognition Research. It manifests models used in our experiments.

Emotion-classification-in-EEG-signals

Emotion-Recognition-based-on-EEG-using-Generative-Adversarial-Nets-and-Convolutional-Neural-Network

Emotion recognition plays an important role in the field of human-computer interaction (HCI). Automatic emotion recognition based on EEG is an important topic in brain-computer interface (BCI) applications.Currently, deep learning has been widely used in the field of EEG emotion recognition and has achieved remarkable results. However, due to the small amount of EEG data and the serious imbalance in the proportion of EEG data categories, it is difficult to use deeper models. In addition, we believe that there is a frequency band correlation feature between the EEG signal frequency bands, which has an important effect on EEG emotion recognition. In this paper, we first proposed an adversarial neural network model for sample generation. Because we used PSD features in the experiment, this generative model is called PSD-GAN. Then we designed FBSCNN(Frequency band separation convolutional neural network) and FBCCNN(Frequency Band Correlation Convolutional Neural Network) models as a comparison to explore the influence of frequency band correlation features on EEG emotion recognition. Among them, FBSCNN can not extract the frequency band correlation features, but FBCCNN can extract the frequency band correlation features. The experimental results show that the samples generated by PSD-GAN have good performance, and the frequency band correlation feature can effectively improve the accuracy of EEG emotion recognition. Moreover, we compare our FBCCNN + PSD-GAN model with similar studies and the results show that our model is highly competitive.

Emotion-Recognition-from-brain-EEG-signals-

Emotion recognition can be achieved by obtaining signals from the brain by EEG . This test records the activity of the brain in form of waves. We have used DEAP dataset on which we are classifying the emotion as valance, likeness/dislike, arousal, dominance. We have used LSTM and CNN classifier which gives 88.60 % accuracy to predict the model successfully.

GAIIC2023

GAIIC赛道一：影像学 NLP — 医学影像诊断报告生成 [A100换你大棚甜瓜 Rank-12 方案]

Gated-Transformer-on-MTS-1

使用改良的Transformer模型应用于多维时间序列的分类任务上

generative-compression

TensorFlow Implementation of Generative Adversarial Networks for Extreme Learned Image Compression

github_PeterL1n_BackgroundMattingV2

high-fidelity-generative-compression

Pytorch implementation of High-Fidelity Generative Image Compression + Routines for neural image compression

PaddleGAN

PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, wav2lip, picture repair, image editing, photo2cartoon, image style transfer, and so on.

Pytorch_LongText_Classification_Demo

Pytorch进行长文本分类。这里用到的网络有：FastText、TextCNN、TextRNN、TextRCNN、Transformer

slider-unlock

基于opencv图像识别的滑块验证码破解Demo

SReC

PyTorch Implementation of "Lossless Image Compression through Super-Resolution"

STS-Transformer-A-spatiotemporal-symmetrical-transformer-structure-for-EEG-emotion-recognition

Tianchi-2021-Guangdong-Tile-Detection

天池2021广东工业智能制造大赛瓷砖瑕疵检测极客奖方案

USRNet

Deep Unfolding Network for Image Super-Resolution (CVPR, 2020) (PyTorch)