lomoda0715

3D-Convnet-for-Alzheimer-s-Detection

product titles

3D-Medical-Imaging-Preprocessing-All-you-need

This Repo Will contain the Preprocessing Code for 3D Medical Imaging

AI-Job-Notes

AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）

AlphaTree-graphic-deep-neural-network

深度神经网络(DNN)与对抗神经网络(GAN)模型总览图示，建立模型发展路书(roadmap),方便大家的理解与学习

AnoDDPM

CVPR Workshop paper - AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise

Blood-cell-image-classification

class-balanced-loss

Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019

Guided-Attention-Inference-Network

Contains implementation of Guided Attention Inference Network (GAIN) presented in Tell Me Where to Look(CVPR 2018). This repository aims to apply GAIN on fcn8 architecture used for segmentation.

L2C

Learning to Cluster. A deep clustering strategy.

TensorFlow-Course

Simple and ready-to-use tutorials for TensorFlow

lomoda0715/L2C

Learning to Cluster. A deep clustering strategy.

lomoda0715/3D-Medical-Imaging-Preprocessing-All-you-need

This Repo Will contain the Preprocessing Code for 3D Medical Imaging

lomoda0715/AlphaTree-graphic-deep-neural-network

深度神经网络(DNN)与对抗神经网络(GAN)模型总览图示，建立模型发展路书(roadmap),方便大家的理解与学习

lomoda0715/AnoDDPM

CVPR Workshop paper - AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise

lomoda0715/Blood-cell-image-classification

lomoda0715/coatnet-pytorch

A PyTorch implementation of "CoAtNet: Marrying Convolution and Attention for All Data Sizes".

lomoda0715/Coding-Now

学习记录的一些笔记，以及所看得一些电子书eBooks、视频资源和平常收纳的一些自己认为比较好的博客、网站、工具。涉及大数据几大组件、Python机器学习和数据分析、Linux、操作系统、算法、网络等

lomoda0715/CTseg

Brain CT image segmentation, normalisation, skull-stripping and total brain/intracranial volume computation.

lomoda0715/External-Attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

lomoda0715/FixRes

This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423

lomoda0715/google-research

Google Research

lomoda0715/Graph-Neural-Network-Note

A blog for understanding graph neural network

lomoda0715/guided-diffusion

lomoda0715/LDAM-DRW

[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

lomoda0715/medical-data

lomoda0715/ModelsGenesis

Official Keras Implementation and Pre-trained Models for Models Genesis - MICCAI 2019

lomoda0715/mws

Code for paper in CVPR2019, 'Multi-source weak supervision for saliency detection'

lomoda0715/nvidia-docker

Build and run Docker containers leveraging NVIDIA GPUs

lomoda0715/OpenLongTailRecognition-OLTR

Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)

lomoda0715/process_head_ct

lomoda0715/pumpkin-book

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book

lomoda0715/pytorch-grad-cam

Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

lomoda0715/pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

lomoda0715/RIDE-LongTailRecognition

[ICLR 2021 Spotlight] Pytorch implementation for "Long-tailed Recognition by Routing Diverse Distribution-Aware Experts."

lomoda0715/smote_variants

A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features

lomoda0715/STEGO

Unsupervised Semantic Segmentation by Distilling Feature Correspondences

lomoda0715/Swin-Transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

lomoda0715/taichi

The Taichi programming language

lomoda0715/vision

Datasets, Transforms and Models specific to Computer Vision

lomoda0715/vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch