Categories
Development Tools
Algorithms & Data Structures
ML Engineering & MLOps
Problem Solving
Python
Machine Learning
Generative Models
Multimodal AI
Natural Language Processing
Data Engineering & Analytics
Recommender Systems
Probabilistic ML & Statistics
Graph Machine Learning
Investing
Blockchain
Computer Vision
Development Tools
- PyCharm 사용법 2 - 단축키 27 Apr 2023
- 2023년 상반기 쓸만한 AI 도구들 26 Apr 2023
- Linux(Ubuntu) terminal 명령어 정리 18 May 2021
- Latex 사용법(레이텍, 라텍 사용법) 16 Dec 2020
- GitHub 사용법 - 09. Overall(Git 명령어 정리, Git 사용법) 27 May 2020
- PyCharm 사용법(파이참 설치 및 사용법) 07 Feb 2019
- Miniconda(Anaconda) 사용법(conda 설치 및 사용법) 01 Feb 2019
- Jupyter Notebook 사용법(주피터 노트북 설치 및 사용법) 26 Jan 2019
- GitHub 사용법 - 09. Fork, Pull Requests 20 Aug 2018
- GitHub 사용법 - 08. Conflict 19 Aug 2018
- GitHub 사용법 - 07. diff, add, commit, .gitignore 중급 15 Aug 2018
- GitHub 사용법 - 06. branch 관리 12 Aug 2018
- GitHub 사용법 - 05. branch 기본 2 11 Aug 2018
- GitHub 사용법 - 04. branch 기본 1 07 Aug 2018
- GitHub 사용법 - 03. 프로젝트 clone, status check, .gitignore 08 Jul 2018
- Markdown 사용법 29 Jun 2018
- GitHub 사용법 - 02. 프로젝트와 repository 생성 29 Jun 2018
- GitHub 사용법 - 01. 소개 29 Jun 2018
- GitHub 사용법 - 00. Command List 29 Jun 2018
- Github blog 수식 입력 방법 29 Jun 2018
- example-title 28 Jun 2018
- Introducing Lanyon 02 Jan 2014
- Example content 01 Jan 2014
- What's Jekyll? 31 Dec 2013
Algorithms & Data Structures
- 디닉 알고리즘(Dinic's Algorithm) 11 Jul 2018
- 펜윅 트리(Fenwick Tree, Binary Indexed Tree, BIT) 09 Jul 2018
- greeksharifa's Library 07 Jul 2018
- 고속 푸리에 변환(Fast Fourier Theorem, FFT). 큰 수의 곱셈 07 Jul 2018
- 행렬의 N 거듭제곱 빠르게 구하기 04 Jul 2018
- Stack(스택) 29 Jun 2018
ML Engineering & MLOps
- MMDetection 사용법 2(Tutorial) 05 Sep 2021
- MMDetection 사용법 1(Quick Run) 30 Aug 2021
- Minikube 설치하기 12 Aug 2021
- Kubeflow 튜토리얼1 12 Aug 2021
- WSL2 Ubuntu 환경에서 Kubeflow 설치하기 05 Aug 2021
- Pytorch를 위한 Docker 사용법(Pytorch 도커 사용법) 21 Jun 2021
- Weight & Biases(wandb) 사용법(wandb 설치 및 설명) 10 Jun 2020
- PyTorch 사용법 - 04. Recurrent Neural Network(RNN) Model 12 Jun 2019
- PyTorch 사용법 - 03. How to Use PyTorch 10 Nov 2018
- PyTorch 사용법 - 02. Linear Regression Model 02 Nov 2018
- PyTorch 사용법 - 01. 소개 및 설치 02 Nov 2018
- PyTorch 사용법 - 00. References 02 Nov 2018
- TensorFlow 사용법 - 01. 소개 및 설치 10 Jul 2018
- PyTorch 사용법 - 02. Tensor 생성 함수 05 Jul 2018
Problem Solving
- BOJ 01000(A+B), 01001(A-B), 01002(터렛) 문제 풀이 16 Aug 2018
- BOJ 06086(최대 유량) 문제 풀이 12 Jul 2018
- BOJ 11658(구간 합 구하기 3) 문제 풀이 11 Jul 2018
- BOJ 01280(나무 심기) 문제 풀이 11 Jul 2018
- BOJ 02042(구간 합 구하기) 문제 풀이 10 Jul 2018
- BOJ 13277(큰 수 곱셈) 문제 풀이 08 Jul 2018
- BOJ 10828(스택) 문제 풀이 08 Jul 2018
- BOJ 09012(괄호) 문제 풀이 08 Jul 2018
- BOJ 06549(히스토그램에서 가장 큰 직사각형) 문제 풀이 07 Jul 2018
Python
- gspread 사용법(python gspread - google spreadsheet) 10 Apr 2023
- Python 프로젝트 생성하기 18 Jul 2022
- Python glob, os, platform, shutil 사용법(Python os 다루기) 07 Apr 2022
- Python time, datetime 사용법(Python 시간 다루기) 18 May 2021
- Python 영상·음성 처리 실무 가이드(FFmpeg, MoviePy, OpenCV, PyAV, librosa) 09 May 2021
- Python Selenium 사용법 [파이썬 셀레늄 사용법, 크롤링] 30 Oct 2020
- 파이썬 Error 처리 12 Jan 2020
- 파이썬 압축 모듈 간단 예시 11 Jan 2020
- 파이썬 collections, heapq 모듈 설명 10 Jan 2020
- 파이썬 numba 모듈 설명 16 Dec 2019
- 파이썬 logging Module 설명 13 Dec 2019
- Python argparse 사용법 12 Feb 2019
- 파이썬 정규표현식(re) 사용법 - 09. 기타 기능 24 Aug 2018
- 파이썬 정규표현식(re) 사용법 - 08. 예제(단어, 행) 06 Aug 2018
- 파이썬 정규표현식(re) 사용법 - 07. 예제(숫자) 06 Aug 2018
- 파이썬 정규표현식(re) 사용법 - 06. 치환 함수, 양방탐색, 조건문 05 Aug 2018
- 파이썬 정규표현식(re) 사용법 - 05. 주석, 치환, 분리 04 Aug 2018
- 파이썬 정규표현식(re) 사용법 - 04. 그룹, 캡처 28 Jul 2018
- 파이썬 정규표현식(re) 사용법 - 03. OR, 반복 22 Jul 2018
- 파이썬 정규표현식(re) 사용법 - 02. 문자, 경계, flags 21 Jul 2018
- 파이썬 정규표현식(re) 사용법 - 01. Basic 20 Jul 2018
Machine Learning
- Summary explanation: RelateAnything: Real-Time Open-Vocabulary Relation Prediction From Any Inputs 11 Sep 2026
- RelateAnything: Real-Time Open-Vocabulary Relation Prediction From Any Inputs 요약 설명 11 Sep 2026
- Summary explanation: Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation 08 Sep 2026
- Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation 요약 설명 08 Sep 2026
- Summary explanation: AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing 08 Sep 2026
- AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing 요약 설명 08 Sep 2026
- Summary explanation: A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms 03 Sep 2026
- A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms 요약 설명 03 Sep 2026
- Summary explanation: Language Models Can Control Their Own Attention 02 Sep 2026
- Language Models Can Control Their Own Attention 요약 설명 02 Sep 2026
- Summary explanation: Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning 27 Aug 2026
- Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning 요약 설명 27 Aug 2026
- Summary explanation: EnvHarness: Awakening Static Worlds for Agent Learning 20 Aug 2026
- EnvHarness: Awakening Static Worlds for Agent Learning 요약 설명 20 Aug 2026
- Summary explanation: 4DAnyone: Create Anyone in 4D from a Casual Monocular Video 20 Aug 2026
- 4DAnyone: Create Anyone in 4D from a Casual Monocular Video 요약 설명 20 Aug 2026
- Summary explanation: SPADE: Self-Play in Adaptive Synthetic Executable Environments 19 Aug 2026
- SPADE: Self-Play in Adaptive Synthetic Executable Environments 요약 설명 19 Aug 2026
- Summary explanation: PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX 18 Aug 2026
- PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX 요약 설명 18 Aug 2026
- Agent Lightning v1.0: Towards Harnessed Agentic RL 요약 설명 18 Aug 2026
- Summary explanation: Zetta $\zeta$: An Efficient Closed-Loop Embodied Harness for Self-Evolving Physical Intelligence 17 Aug 2026
- Zetta $\zeta$: An Efficient Closed-Loop Embodied Harness for Self-Evolving Physical Intelligence 요약 설명 17 Aug 2026
- Summary explanation: Specification-first convergence with an AI coding agent: a case study of dismantling a core architectural invariant across 189 files in a 717k-line codebase with no test oracle and no human code review 12 Aug 2026
- Specification-first convergence with an AI coding agent: a case study of dismantling a core architectural invariant across 189 files in a 717k-line codebase with no test oracle and no human code review 요약 설명 12 Aug 2026
- Summary explanation: Agent Safety Should Be a Runtime Contract 11 Aug 2026
- Agent Safety Should Be a Runtime Contract 요약 설명 11 Aug 2026
- Summary explanation: SWE-Bench ProMax: Benchmarking Agents on Large-Scale Multilingual Code Refactoring 10 Aug 2026
- SWE-Bench ProMax: Benchmarking Agents on Large-Scale Multilingual Code Refactoring 요약 설명 10 Aug 2026
- Summary explanation: HarnessOpt-Bench: Evaluating LLMs at Harness Optimization 06 Aug 2026
- HarnessOpt-Bench: Evaluating LLMs at Harness Optimization 요약 설명 06 Aug 2026
- PAST-Bench: Benchmarking the Foundations of Recursive Self-Improvement in Personal Agents 요약 설명 04 Aug 2026
- Summary explanation: AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling 03 Aug 2026
- AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling 요약 설명 03 Aug 2026
- Summary explanation: Echoverse: Deep, Evolving Environments for Training Computer-Use Agents at Scale 30 Jul 2026
- Echoverse: Deep, Evolving Environments for Training Computer-Use Agents at Scale 요약 설명 30 Jul 2026
- Summary explanation: Can AI agents conduct open-ended AI research? Early evidence from two case studies 29 Jul 2026
- Can AI agents conduct open-ended AI research? Early evidence from two case studies 요약 설명 29 Jul 2026
- Summary explanation: StateAct: Program State, before Pixels, for Long-Horizon Computer-Use Agents 24 Jul 2026
- StateAct: Program State, before Pixels, for Long-Horizon Computer-Use Agents 요약 설명 24 Jul 2026
- Summary explanation: Progress Reward Modeling for Robotic Learning: A Comprehensive Survey 22 Jul 2026
- Progress Reward Modeling for Robotic Learning: A Comprehensive Survey 요약 설명 22 Jul 2026
- Summary explanation: Two-Level Meta-Rubrics for Evaluating Open-Ended Generation: GAMUT, a Benchmark for Factual Completeness 21 Jul 2026
- Two-Level Meta-Rubrics for Evaluating Open-Ended Generation: GAMUT, a Benchmark for Factual Completeness 요약 설명 21 Jul 2026
- Summary explanation: Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing 21 Jul 2026
- Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing 요약 설명 21 Jul 2026
- Summary explanation: LLM-as-a-Coach: Experiential Learning for Non-Verifiable Tasks 20 Jul 2026
- LLM-as-a-Coach: Experiential Learning for Non-Verifiable Tasks 요약 설명 20 Jul 2026
- GTN(Gated Transformer Networks for Multivariate Time Series Classification) 요약 설명 31 Aug 2022
- Contrastive Learning, SimCLR 논문 설명(SimCLRv1, SimCLRv2) 09 Dec 2021
- Metric Learning 설명 06 Dec 2021
- Margin-based Loss 설명 24 Oct 2021
- BLEURT - Learning Robust Metrics for Text Generation(BLEU 개선 버전, BLEURT 논문 설명) 13 Jan 2021
- Self-Supervised Learning(자기지도 학습 설명) 01 Nov 2020
- Deep Learning(Ian Goodfellow) 책 정리 - 01. Introduction 02 Oct 2020
- EM (Expected Maximization) 알고리즘 설명 28 Jul 2020
- Light GBM 설명 및 사용법 09 Dec 2019
- Imbalanced Learning 01 Oct 2019
- Contextual Bandit and Tree Heuristic 18 Sep 2019
- 2019 ICML Papers(ICML 2019 논문 설명) 11 Jul 2019
- Bootstrap, Bagging, Boosting 06 Nov 2018
Generative Models
- VQ-VAE 2 논문 설명(Generating Diverse High-Fidelity Images with VQ-VAE-2) 26 Nov 2021
- VQ-VAE 논문 설명(Neural Discrete Representation Learning) 07 Nov 2021
- Adversarial AutoEncoder (AAE) 설명 23 Aug 2020
- Conditional Variational AutoEncoder (CVAE) 설명 07 Aug 2020
- Variational AutoEncoder (VAE) 설명 31 Jul 2020
- Pix2Pix(Image-to-Image Translation with Conditional Adversarial Networks, Pix2Pix 논문 설명) 07 Apr 2019
- GAN의 개선 모델들(catGAN, Semi-supervised GAN, LSGAN, WGAN, WGAN_GP, DRAGAN, EBGAN, BEGAN, ACGAN, infoGAN), GAN의 개선 모델 설명 20 Mar 2019
- f-GAN(f-GAN 논문 설명) 19 Mar 2019
- CGAN(Conditional GAN), C-GAN 논문 설명 19 Mar 2019
- DCGAN(Deep Convolutional GAN, DCGAN 논문 설명) 17 Mar 2019
- GAN(Generative Adversarial Networks), GAN 논문 설명 03 Mar 2019
Multimodal AI
- AGQA 2.0 - An Updated Benchmark for Compositional Spatio-Temporal Reasoning 설명 06 Mar 2023
- AGQA - A Benchmark for Compositional Spatio-Temporal Reasoning 설명 03 Mar 2023
- Learning to Retrieve Videos by Asking Questions 논문 설명 10 Aug 2022
- StyleCLIP 논문 리뷰(StyleCLIP - Text-Driven Manipulation of StyleGAN Imagery) 24 Dec 2021
- CLIP 논문 리뷰(Learning Transferable Visual Models From Natural Language Supervision) 19 Dec 2021
- VideoBERT - A Joint Model for Video and Language Representation Learning, CBT(Learning Video Representations using Contrastive Bidirectional Transformer) 논문 설명 13 Dec 2021
- VL-BERT, ViL-BERT 논문 설명(VL-BERT - Pre-training of Generic Visual-Linguistic Representations, ViLBERT - Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks) 12 Dec 2021
- HERO 논문 설명(HERO - Hierarchical Encoder for Video+Language Omni-representation Pre-training) 15 Aug 2021
- VATT 논문 설명(VATT - Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text) 04 Aug 2021
- ERNIE 논문 설명(ERNIE-ViL- Knowledge Enhanced Vision-Language Representations Through Scene Graph) 19 Jul 2021
- KnowIT VQA - Answering Knowledge-Based Questions about Videos(KnowIT VQA 논문 설명) 24 Nov 2020
- KVQA - Knowledge-Aware Visual Question Answering(KVQA 논문 설명) 17 Nov 2020
- MovieQA(Movie Question Answering, MovieQA 논문 설명) 29 May 2019
- VQA(Visual Question Answering, VQA 논문 설명) 17 Apr 2019
- DANs(Dual Attention Networks for Multimodal Reasoning and Matching, DANs 논문 설명) 17 Apr 2019
Natural Language Processing
- Tree of Thoughts - Deliberate Problem Solving with Large Language Models (ToT) 요약 설명 19 Mar 2025
- Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena (LLM-as-a-Judge) 요약 설명 18 Mar 2025
- Adapting-large-language-models-to-domains-via-reading-comprehension 요약 설명 17 Jan 2025
- LoRA - Low-Rank Adaptation of Large Language Models 요약 설명 21 Sep 2022
- ScaleNorm - Transformers without Tears(Improving the Normalization of Self-Attention) 요약 설명 21 Aug 2022
- Linformer(Self-Attention with Linear Complexity) 요약 설명 18 Aug 2022
- Fastformer(Additive Attention Can Be All You Need) 요약 설명 18 Aug 2022
- Synthesizer(Rethinking self-attention for transformer models) 요약 설명 17 Aug 2022
- BART 논문 설명(BART - Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension) 09 Aug 2022
- Minerva 논문 설명(Solving Quantitative Reasoning Problems with Language Models) 10 Jul 2022
- ERNIE 논문 설명(ERNIE 3.0 - Large-Scale Knowledge Enhanced Pre-Training For Language Understanding And Generation) 28 Jul 2021
- ERNIE 논문 설명(ERNIE-Doc - A Retrospective Long-Document Modeling Transformer) 25 Jul 2021
- ERNIE 논문 설명(ERNIE 2.0 - A Continual Pre-Training Framework for Language Understanding) 05 Jul 2021
- ERNIE 논문 설명(ERNIE - Enhanced Language Representation with Informative Entities) 01 Jul 2021
- ERNIE 논문 설명(ERNIE - Enhanced Representation through Knowledge Integration) 14 Jun 2021
- OpenAI GPT-3 - Language Models are Few-Shot Learners(GPT3 논문 설명) 14 Aug 2020
- Explain Yourself! Leveraging Language Models for Commonsense Reasoning 08 Feb 2020
- OpenAI GPT-2 - Language Models are Unsupervised Multitask Learners(GPT2 논문 설명) 28 Aug 2019
- BERT - Pre-training of Deep Bidirectional Transformers for Language Understanding(BERT 논문 설명) 23 Aug 2019
- OpenAI GPT-1 - Improving Language Understanding by Generative Pre-Training(GPT1 논문 설명) 21 Aug 2019
- ELMo - Deep contextualized word representations(ELMo 논문 설명) 20 Aug 2019
- Attention Is All You Need(Attention 논문 설명) 17 Aug 2019
- Generating Sequences With Recurrent Neural Networks 15 Jul 2019
Data Engineering & Analytics
- seaborn 사용법(python seaborn 사용법) 13 May 2023
- matplotlib 사용법(python matplotlib.pyplot 사용법) 12 May 2023
- SQL 기본 01 Oct 2021
- AB Test Sample Size 구하기 30 Sep 2021
- AB Test 기본 30 Sep 2021
- Apache Spark 기본 20 Sep 2021
- Seaborn Module 사용법 05 Dec 2019
Recommender Systems
- Recommendation for new users & items via randomized training and M-o-E transformation 요약 설명 19 Aug 2022
- PinnerSage(Multi-modal user embedding framework for recommendations at pinterest) 요약 설명 19 Aug 2022
- DropoutNet(Addressing Cold Start in Recommender Systems) 요약 설명 19 Aug 2022
- Tab-Transformer(Tabular Data Modeling using contextual embeddings) 설명 13 Mar 2022
- Bert4Rec(Sequential Recommendation with BERT) 설명 12 Dec 2021
- BST(Behavior Sequence Transformer for E-commerce Recommendation in Alibaba) 설명 04 Dec 2021
- PCREC(Pre-training Graph Neural Network for Cross Domain Recommendation) 설명 28 Nov 2021
- IGMC (Inductive Graph-based Matrix Completion) 설명 26 Aug 2021
- Session-based Recommendation with GNN (SR-GNN) 설명 03 Jul 2021
- PinSAGE (Graph Convolutional Neural Networks for Web-Scale Recommender Systems) 설명 21 Feb 2021
- Graph Convolutional Matrix Completion (GCMC) 설명 06 Dec 2020
- Logistic Matrix Factorization 설명 02 Jun 2020
- LightFM 설명 01 Jun 2020
- Attentional Factorization Machines (AFM) 논문 리뷰 및 Tensorflow 구현 01 May 2020
- DeepFM 논문 리뷰 및 Tensorflow 구현 07 Apr 2020
- Field-aware Factorization Machines (FFM) 설명 및 xlearn 실습 05 Apr 2020
- Factorization Machines (FM) 설명 및 Tensorflow 구현 21 Dec 2019
- Matrix Factorization 설명 및 논분 리뷰 20 Dec 2019
- 잠재요인 협업필터링 (Latent Factor Collaborative Filtering) 설명 17 Dec 2019
Probabilistic ML & Statistics
- Monte Carlo Approximation (몬테카를로 근사 방법) 설명 30 Jul 2020
- Variational Inference (변분 추론) 설명 14 Jul 2020
- Gaussian Process 설명 12 Jul 2020
Graph Machine Learning
- Strategies for pre-training Grapn Neural Networks 설명 01 Feb 2022
- Graphormer(Do Transformers Really Perform Bad for Graph Representation?) 설명 30 Jan 2022
- metapath2vec(Scalable Representation Learning for Heterogeneous Networks) 설명 11 Dec 2021
- HGT(Heterogeneous Graph Transformer) 설명 02 Oct 2021
- SIGN(Scalable Inception Graph Neural Networks) 설명 10 Sep 2021
- Graph Pooling - gPool, DiffPool, EigenPool 설명 09 Sep 2021
- GTN(Graph Transformer Networks) 설명 08 Sep 2021
- Pytorch Geometric custom graph convolutional layer 생성하기 05 Sep 2021
- Pytorch Geometric Message Passing 설명 04 Sep 2021
- APPNP(Predict Then Propagate) 설명 20 Aug 2021
- ClusterGCN 설명 15 Aug 2021
- Graph Fourier Transform 설명 14 Aug 2021
- Graph Diffusion Convolution (GDC) 설명 12 Aug 2021
- Graph Isomorphism Network (GIN) 설명 05 Jun 2021
- Graph Attention Networks (GAT) 설명 29 May 2021
- GraphSAGE (Inductive Representation Learning on Large Graphs) 설명 31 Dec 2020
Investing
- Hyperlocal SNS의 대표 주자, nextdoor 09 Aug 2021
- 중국 보험업의 선두 주자, 평안보험(Ping An of China) 23 Apr 2021
- 금리 상승기에 주목해야 하는 ETF, Vanguard Financials ETF (VFH) 04 Apr 2021
Blockchain
- LINK 코인(라인코인) 2021 계획 및 백서 요약 18 May 2021
Computer Vision
- Generalized Out-of-Distribution Detection - A Survey 논문 설명 18 Aug 2022
- Resnet 계열 image classification 모델 설명 26 Jun 2022
- STAR benchmark 논문 설명(STAR - A Benchmark for Situated Reasoning in Real-World Videos) 07 Jun 2022
- EfficientNet 논문 설명(EfficientNet - Rethinking Model Scaling for Convolutional Neural Networks) 01 Mar 2022
- MobileNetV3 논문 설명(Searching for MobileNetV3 리뷰) 23 Feb 2022
- MobileNetV2 논문 설명(MobileNetsV2 - Inverted Residuals and Linear Bottlenecks 리뷰) 10 Feb 2022
- MobileNetV1 논문 설명(MobileNets - Efficient Convolutional Neural Networks for Mobile Vision Applications 리뷰) 01 Feb 2022
- Video Swin Transformer 논문 설명 18 Dec 2021
- Swin Transformer V2 - Scaling Up Capacity and Resolution 논문 설명 15 Dec 2021
- Swin Transformer - Hierarchical Vision Transformer using Shifted Windows 논문 설명 14 Dec 2021
- ViT(Vision Transformer) 논문 설명(An Image is Worth 16x16 Words - Transformers for Image Recognition at Scale) 10 Dec 2021
- ViViT(Video ViT, ViViT - A Video Vision Transformer), MTN, TimeSFormer, MViT 논문 설명 10 Dec 2021
- Attention based Video Models 06 Dec 2021
- RNN based Video Models 04 Dec 2021
- Action Recognition Models(Two-stream, TSN, C3D, R3D, T3D, I3D, S3D, SlowFast, X3D) 04 Dec 2021
- Deep Learning 주요 데이터셋 정리 (2026년 기준) 01 Nov 2021
- CNN 기본 모델(ImageNet Challenge - AlexNet, ZFNet, VGG, GoogLeNet, ResNet, InceptionNet) 24 Oct 2021
- HowTo100M 설명(HowTo100M - Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips, Antoine Miech et al, 7 Jun 2019, 1906.03327) 18 Aug 2021