fancaizi-1

fancaizi-1's Stars

• WZMIAOMIAO/deep-learning-for-image-processing

  deep learning for image processing including classification and object-detection etc.

  Language:Python22.6k1604147.9k

• tangyudi/Ai-Learn

  人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

  9.6k20202.2k

• wyharveychen/CloserLookFewShot

  source code to ICLR'19, 'A Closer Look at Few-shot Classification'

  Language:Python1.1k1974269

• barebell/DA

  Unsupervised Domain Adaptation Papers and Code

  753409176

• AaronCosmos/wdcnn_bearning_fault_diagnosis

  wdcnn轴承故障模型

  Language:Python3328095

• SNBQT/Limited-Data-Rolling-Bearing-Fault-Diagnosis-with-Few-shot-Learning

  This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning

  Language:Jupyter Notebook2835645

• ZhangWei1993/Mechanical-Fault-Diagnosis-Based-on-Deep-Learning

  CNN for mechanical fault diagnosis

  Language:Python28112685

• liguge/Deep-Residual-Shrinkage-Networks-for-intelligent-fault-diagnosis-DRSN-

  Deep Residual Shrinkage Networks for Intelligent Fault Diagnosis（pytorch） 深度残差收缩网络应用于故障诊断

  Language:Python1921830

• fyancy/MetaFD

  The source codes of Meta-learning for few-shot cross-domain fault diagnosis.

  Language:Python1281628

• IbrahimSobh/imageclassification

  Deep Learning: Image classification, feature visualization and transfer learning with Keras

  Language:Jupyter Notebook1228033

• zggg1p/A-Domain-Adaption-Transfer-Learning-Bearing-Fault-Diagnosis-Model-Based-on-Wide-Convolution-Deep-Neu

  Inspired by the idea of transfer learning, a combined approach is proposed. In the method, Deep Convolutional Neural Networks with Wide First-layer Kernel is used to extract features to classify the health conditions.

  Language:Python1022414

• Tony607/Focal_Loss_Keras

  Multi-class classification with focal loss for imbalanced datasets

  Language:Jupyter Notebook823536

• koshian2/affinity-loss

  Unofficial implementation of "Max-margin Class Imbalanced Learning with Gaussian Affinity"

  Language:Python725516

• OzerCanDevecioglu/Zero-Shot-Bearing-Fault-Detection-by-Blind-Domain-Transition

  Language:Python32136

• devamsheth21/Bearing-Fault-Detection-using-Deep-Learning-approach

  Detection and multi-class classification of Bearing faults using Image classification from Case Western Reserve University data of bearing vibrations recorded at different frequencies. Developed an algorithm to convert vibrational data into Symmetrized Dot Pattern images based on a Research paper. Created an Image dataset of 50 different parameters and 4 different fault classes, to select optimum parameters for efficient classification. Trained and tested 50 different datasets on different Image-net models to obtain maximum accuracy. Obtained an accuracy of 98% for Binary classification of Inner and Outer race faults on Efficient Net B7 model on just 5 epochs.

  Language:Jupyter Notebook19107

• Chirag-Shilwant/One-Shot-Classification-using-Siamese-Network-on-MNIST-Dataset

  A Siamese Neural Network is a class of neural network architectures that contain two or more identical subnetworks. ‘identical’ here means, they have the same configuration with the same parameters and weights.

  Language:Jupyter Notebook10114

• 123EastGod/Digital-twin-assisted-imbalanced-fault-diagnosis-framework

  一种数字孪生辅助的高度不平衡故障诊断新框架

  Language:Python7001

• subaandhvk/FewShotLearning_Image_Classification

  Language:Jupyter Notebook6001

• jsivaku1/kNNMTD

  Language:Python5114