StoneHammer's repositories
18bMachineLearning
Lecture Note&Code
AlignGAN
[ICCV2019] RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment
H410D4IPC_i5-10400_HD630_OpenCore
昂达H410D4 IPC + i5 10400 核显
Hetero-center-loss-for-cross-modality-person-re-id
Code for paper "Hetero-center loss for cross-modality person re-identification"
kits19
The official repository of the 2019 Kidney and Kidney Tumor Segmentation Challenge
labelme
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
lung_class
lung
MAE-pytorch
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
marLo
Multi Agent Reinforcement Learning using MalmÖ
Mask-RCNN
A PyTorch implementation of the architecture of Mask RCNN
Mask_RCNN
Mask R-CNN on Keras and TensorFlow，个人注释版
NAS_FPN_Tensorflow
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection.
Pneumonia-Diagnosis-using-XRays-96-percent-Recall
BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.
pytorch-center-loss
Pytorch implementation of Center Loss
ReadDiff
生成模型的读书笔记，主要使用markdown，请使用jupyter做demo
reid-strong-baseline
Bag of Tricks and A Strong Baseline for Deep Person Re-identification
RWDiff
rw-diff code
SHOT
code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"
social-relation-tensorflow
Social Relation Recognition TensorFlow
UGATIT-pytorch
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
Usiigaci
Usiigaci: stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning
WS-DAN.PyTorch
A PyTorch implementation of WS-DAN (Weakly Supervised Data Augmentation Network) for FGVC (Fine-Grained Visual Classification)