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tenfoldm's Projects

adl icon adl

Attention-based Dropout Layer for Weakly Supervised Object Localization (CVPR 2019 Oral)

ag-cnn icon ag-cnn

This is a reimplementation of AG-CNN. ("Thorax Disease Classification with Attention Guided Convolutional Neural Network","Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification")

annotated_deep_learning_paper_implementations icon annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

awesome_llms_interview_notes icon awesome_llms_interview_notes

LLMs interview notes and answers:该仓库主要记录大模型(LLMs)算法工程师相关的面试题和参考答案

bevformer icon bevformer

[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.

chexnet icon chexnet

A pytorch reimplementation of CheXNet

chexnet-1 icon chexnet-1

Implementation of the CheXNet network (PyTorch)

course icon course

高性能并行编程与优化 - 课件

cpp.playground icon cpp.playground

:octocat: educational repo for storing my practice sessions with ASM, C and C++ as well as solutions to online courses I take relating to ASM, C, and C++ programming

danet icon danet

Dual Attention Network for Scene Segmentation (CVPR2019)

espnet icon espnet

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

fcanet icon fcanet

Simple reimplemetation experiments about FcaNet

ffa-net icon ffa-net

FFA-Net: Feature Fusion Attention Network for Single Image Dehazing

interview-for-algorithm-engineer icon interview-for-algorithm-engineer

AIGC,传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、图像处理、元宇宙、SLAM等AI面试经验分享

jsrt-parser icon jsrt-parser

This is a data parser to obtain images and descriptions from JSRT database in a uniform format for deep learning applications.

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