Created: 2026-05-23
This queue translates the expanded traffic goal into paired Korean and English topic sets. It began as a 50-pair campaign, but production now intentionally exceeds that baseline as fields are expanded toward roughly 30 or more topic pairs each. The current site now keeps the existing troubleshooting strength, then adds AI trends, global affairs, climate and energy, consumer rights, digital security, personal finance, health literacy, study, economy, and Easy Labeling computer vision content.
translation_id.header.teaser, header.overlay_image, and once near the opening section when it clarifies the concept.npm run validate:content-plan; run bundle exec jekyll build --trace before closing a major field or goal milestone.Snapshot date: 2026-05-23 after the Easy Labeling expansion.
| Domain | Topic pairs | Post files | Search intent |
|---|---|---|---|
| Troubleshooting | 150 | 300 | Immediate problem solving |
| AI trends and workflow | 30 | 60 | Current AI adoption and practical implementation |
| Global affairs | 30 | 60 | World issues translated into practical Korea-facing channels |
| Climate and energy | 38 | 76 | Official-source climate, grid, energy, and industry risk explainers |
| Consumer rights | 30 | 60 | Refunds, disputes, subscriptions, recalls, and complaint escalation |
| Digital security | 30 | 60 | Phishing, passwords, MFA, backups, privacy, and cyber hygiene |
| Personal finance | 30 | 60 | Educational budgeting, credit, debt, scam, and investing-risk basics |
| Health literacy | 30 | 60 | Educational health routines, prevention, safety, and care preparation |
| Study and productivity | 32 | 64 | Evidence-informed study systems and exam preparation |
| Economy and money basics | 36 | 72 | Official-source economic indicators and household cost explanations |
| Easy Labeling and computer vision | 37 | 74 | Product-led computer vision data quality and tool discovery |
| Total | 473 | 946 | Broad bilingual growth portfolio |
The detailed tables below preserve the original campaign seeds and the fully expanded Study, Economy, and Easy Labeling queues. The other field expansions are represented by their committed generator scripts and category hubs.
| Status | Translation ID | Primary keyword | Korean title direction | English title direction | Image direction |
|---|---|---|---|---|---|
| review | python-pip-install-failed | pip install failed | Python pip install 실패 해결 |
How to Fix pip install Failed in Python | terminal error + package flow |
| review | python-no-module-named-pip | No module named pip | No module named pip 해결 |
How to Fix No module named pip | Python interpreter and pip module |
| review | python-venv-not-activating | python venv not activating | Python 가상환경이 활성화되지 않을 때 | Python venv Not Activating | virtual environment path map |
| review | python-command-not-found-windows | python command not found windows | Windows에서 python 명령어가 안 될 때 |
Python Command Not Found on Windows | Windows PATH diagram |
| review | python-externally-managed-environment | externally-managed-environment | externally-managed-environment 해결 |
Fix externally-managed-environment in Python | system Python vs venv |
| review | javascript-npm-err-eresolve | npm ERR ERESOLVE | npm ERR! ERESOLVE 해결 |
How to Fix npm ERR ERESOLVE | dependency conflict graph |
| review | node-cannot-find-module | Cannot find module node | Cannot find module 해결 |
Fix Cannot Find Module in Node.js | Node module resolution |
| review | typescript-cannot-find-name | TypeScript Cannot find name | TypeScript Cannot find name 해결 |
Fix TypeScript Cannot Find Name | TypeScript scope diagram |
| review | typescript-property-does-not-exist | Property does not exist on type | Property does not exist on type 해결 |
Fix Property Does Not Exist on Type | object type mismatch |
| review | typescript-tsconfig-paths-not-working | tsconfig paths not working | tsconfig paths가 동작하지 않을 때 |
tsconfig Paths Not Working | tsconfig path alias map |
| review | github-actions-build-failed | GitHub Actions build failed | GitHub Actions build failed 해결 | How to Fix GitHub Actions Build Failed | CI pipeline failure |
| review | github-pages-jekyll-build-failed | GitHub Pages Jekyll build failed | GitHub Pages Jekyll build 실패 | Fix GitHub Pages Jekyll Build Failed | Jekyll build pipeline |
| review | git-fatal-authentication-failed | git fatal authentication failed | fatal: authentication failed 해결 |
Fix Git fatal authentication failed | credential flow |
| review | git-gh006-protected-branch | GH006 protected branch | GH006 protected branch hook declined 해결 |
Fix GH006 Protected Branch Hook Declined | protected branch gate |
| review | spring-boot-port-8080-already-in-use | Spring Boot port 8080 already in use | Spring Boot port 8080 already in use 해결 | Fix Spring Boot Port 8080 Already in Use | port conflict map |
| review | gradle-build-failed | Gradle build failed | Gradle build failed 해결 | How to Fix Gradle Build Failed | Gradle task pipeline |
| review | maven-dependency-not-found | Maven dependency not found | Maven dependency not found 해결 | Fix Maven Dependency Not Found | Maven repository lookup |
| review | java-unsupported-class-file-major-version | unsupported class file major version | Unsupported class file major version 해결 | Fix Unsupported Class File Major Version | JDK version ladder |
| review | docker-daemon-not-running | Docker daemon not running | Docker daemon not running 해결 | Fix Docker Daemon Not Running | Docker client/server |
| review | vscode-python-interpreter-not-showing | VS Code Python interpreter not showing | VS Code Python interpreter 선택 문제 | VS Code Python Interpreter Not Showing | VS Code interpreter picker |
Production source: tools/generate_ai_trends_posts.py.
The table below records the original seed set; the generator now expands this field to 30 paired Korean and English posts.
| Status | Translation ID | Primary keyword | Korean title direction | English title direction | Image direction |
|---|---|---|---|---|---|
| review | ai-agent-workflow-2026 | AI agent workflow | AI agent workflow 2026: 자동화보다 검증이 먼저 | AI Agent Workflow 2026: Build for Verification First | generated workflow diagram |
| review | openai-responses-api-guide | OpenAI Responses API | OpenAI Responses API 사용 흐름 | OpenAI Responses API Practical Guide | request-response flow |
| review | ai-tools-function-calling | AI tool calling | AI tool calling과 function calling 차이 | AI Tool Calling vs Function Calling | tool routing diagram |
| review | rag-evaluation-checklist | RAG evaluation checklist | RAG 답변 품질 평가 체크리스트 | RAG Evaluation Checklist | retrieval and answer scoring |
| review | local-llm-vs-cloud-llm | local LLM vs cloud LLM | Local LLM과 Cloud LLM 선택 기준 | Local LLM vs Cloud LLM | tradeoff matrix |
| review | ai-coding-agent-workflow | AI coding agent workflow | AI coding agent를 안전하게 쓰는 워크플로우 | AI Coding Agent Workflow | coding review loop |
| review | ai-search-optimization | AI search optimization | AI 검색 시대의 글 작성 기준 | How to Write for AI Search | content answer blocks |
| review | prompt-engineering-checklist | prompt engineering checklist | Prompt engineering 실무 체크리스트 | Prompt Engineering Checklist | prompt structure board |
| review | ai-automation-roi | AI automation ROI | AI 자동화 ROI 계산법 | How to Calculate AI Automation ROI | process cost chart |
| review | ai-meeting-notes-workflow | AI meeting notes workflow | AI 회의록 자동화 워크플로우 | AI Meeting Notes Workflow | meeting to action pipeline |
Production source: tools/generate_study_posts.py.
| Status | Translation ID | Primary keyword | Korean title direction | English title direction | Image direction |
|---|---|---|---|---|---|
| review | active-recall-study-method | ActiveRecall | Active Recall 공부법: 읽은 내용을 덮고 꺼내 쓰는 루틴 | Active Recall Study Method: Close the Book and Retrieve | study routine diagram |
| review | spaced-repetition-schedule | SpacedRepetition | Spaced Repetition 복습 일정: 몰아보기보다 간격을 설계하기 | Spaced Repetition Schedule: Design Gaps Instead of Cramming | study routine diagram |
| review | pomodoro-deep-work | Focus | Pomodoro와 Deep Work: 타이머보다 방해 차단이 먼저다 | Pomodoro and Deep Work: Block Distractions Before Timing | study routine diagram |
| review | exam-mistake-note-system | ExamPrep | 오답노트 시스템: 틀린 문제를 다시 틀리지 않는 기록법 | Exam Mistake Note System: Turn Wrong Answers into Review Tasks | study routine diagram |
| review | coding-study-roadmap | CodingStudy | 코딩 공부 로드맵: 문법, 프로젝트, 디버깅을 한 루프로 묶기 | Coding Study Roadmap: Connect Syntax, Projects, and Debugging | study routine diagram |
| review | english-vocabulary-system | Vocabulary | 영어 단어 반복 시스템: 뜻 암기보다 문맥과 회상으로 남기기 | English Vocabulary System: Learn Words Through Context and Recall | study routine diagram |
| review | notion-study-dashboard | Notion | Notion 공부 대시보드: 예쁜 화면보다 복습과 오답 흐름 | Notion Study Dashboard: Track Review and Mistakes Before Design | study routine diagram |
| review | weekly-study-review | WeeklyReview | 주간 공부 회고: 공부 시간보다 회상률과 산출물 보기 | Weekly Study Review: Track Recall and Output, Not Only Hours | study routine diagram |
| review | interleaving-practice | Interleaving | Interleaving Practice: 비슷한 문제를 섞어 진짜 구분력을 키우기 | Interleaving Practice: Mix Similar Problems to Build Discrimination | study routine diagram |
| review | practice-test-review | PracticeTests | 모의고사 리뷰법: 점수보다 틀린 근거를 먼저 분해하기 | Practice Test Review: Break Down Evidence Before Chasing Scores | study routine diagram |
| review | question-bank-system | QuestionBank | 질문은행 만들기: 필기노트를 회상 문제로 바꾸는 법 | Question Bank System: Convert Notes into Recall Prompts | study routine diagram |
| review | semester-study-calendar | StudyPlanning | 학기 공부 캘린더: 시험 직전이 아니라 제출일에서 거꾸로 계획하기 | Semester Study Calendar: Plan Backward from Exams and Deadlines | study routine diagram |
| review | cornell-note-taking-system | CornellNotes | Cornell Note Taking: 필기를 복습 질문으로 바꾸는 구조 | Cornell Note Taking: Turn Notes into Review Questions | study routine diagram |
| review | textbook-reading-output | Reading | 교재 읽기 루틴: 밑줄보다 질문, 요약, 예제로 남기기 | Textbook Reading Routine: Leave Questions, Summary, and Examples | study routine diagram |
| review | lecture-review-24-hour | LectureReview | 강의 후 24시간 리뷰: 잊기 전에 회상 질문 만들기 | 24-Hour Lecture Review: Create Recall Questions Before Forgetting | study routine diagram |
| review | math-problem-solving-routine | MathStudy | 수학 문제 풀이 루틴: 공식 암기보다 조건 해석 먼저 | Math Problem-Solving Routine: Read Conditions Before Formulas | study routine diagram |
| review | writing-revision-study-loop | Writing | 글쓰기 공부 루프: 초안, 피드백, 재작성으로 실력 만들기 | Writing Revision Study Loop: Draft, Feedback, Rewrite | study routine diagram |
| review | coding-kata-deliberate-practice | CodingPractice | Coding Kata 루틴: 같은 문제를 다르게 풀어 패턴을 익히기 | Coding Kata Routine: Solve the Same Problem in Better Ways | study routine diagram |
| review | project-based-learning-portfolio | ProjectBasedLearning | 프로젝트 기반 공부 포트폴리오: 결과물과 회고를 함께 남기기 | Project-Based Learning Portfolio: Keep Output and Reflection Together | study routine diagram |
| review | language-shadowing-routine | LanguageLearning | Language Shadowing 루틴: 따라 말하기를 녹음과 피드백으로 바꾸기 | Language Shadowing Routine: Turn Repetition into Recorded Feedback | study routine diagram |
| review | flashcard-quality-rules | Flashcards | Flashcard 품질 규칙: 카드 수보다 한 카드 한 질문 | Flashcard Quality Rules: One Card, One Question | study routine diagram |
| review | exam-time-management | ExamStrategy | 시험 시간 관리: 어려운 문제보다 시간 손실 지점을 먼저 찾기 | Exam Time Management: Find Where Time Leaks Before Hard Problems | study routine diagram |
| review | sleep-study-performance | Sleep | 수면과 공부 성과: 밤샘보다 기억과 집중을 보호하기 | Sleep and Study Performance: Protect Memory and Attention | study routine diagram |
| review | distraction-audit-study | Focus | 공부 방해요인 감사: 의지보다 환경과 트리거를 고치기 | Study Distraction Audit: Fix Environment and Triggers Before Willpower | study routine diagram |
| review | study-group-rules | StudyGroup | 스터디 그룹 규칙: 친목보다 문제 풀이와 피드백을 남기기 | Study Group Rules: Leave Problem Solving and Feedback | study routine diagram |
| review | metacognition-study-log | Metacognition | Metacognition 공부 로그: 안다고 느낀 것과 실제 회상을 비교하기 | Metacognition Study Log: Compare Confidence with Recall | study routine diagram |
| review | research-note-citation-system | ResearchNotes | 리서치 노트와 출처 관리: 복붙보다 요약과 인용 기준 | Research Note and Citation System: Summarize Before Quoting | study routine diagram |
| review | reading-comprehension-prompts | Reading | 독해력 질문 프롬프트: 글을 읽고 주장, 근거, 반례를 찾기 | Reading Comprehension Prompts: Find Claims, Evidence, and Counterexamples | study routine diagram |
| review | spaced-review-for-coding | CodingStudy | 코딩 개념 Spaced Review: 문법을 프로젝트 안에서 다시 쓰기 | Spaced Review for Coding Concepts: Reuse Syntax in Projects | study routine diagram |
| review | habit-stack-study-routine | StudyHabit | 공부 습관 쌓기: 큰 목표보다 시작 신호와 첫 10분 | Habit Stack Study Routine: Start Signal and First Ten Minutes | study routine diagram |
| review | exam-day-checklist | ExamDay | 시험 당일 체크리스트: 새 공부보다 실수 방지에 집중하기 | Exam Day Checklist: Prevent Mistakes Instead of Adding New Study | study routine diagram |
| review | learning-with-ai-safely | AIStudy | AI로 공부할 때 주의점: 답을 받기보다 질문과 피드백에 쓰기 | Learning with AI Safely: Use It for Questions and Feedback | study routine diagram |
Production source: tools/generate_economy_posts.py.
| Status | Translation ID | Primary keyword | Korean title direction | English title direction | Image direction |
|---|---|---|---|---|---|
| review | interest-rate-inflation-basics | InterestRates | 금리와 물가 기초: 중앙은행 뉴스를 생활비 언어로 읽기 | Interest Rates and Inflation: Read Central Bank News in Household Terms | economy decision diagram |
| review | exchange-rate-basics | ExchangeRates | 환율 기초: 원화 약세가 여행, 수입물가, 수출에 주는 영향 | Exchange Rate Basics: Travel, Import Prices, and Exports | economy decision diagram |
| review | etf-vs-mutual-fund | ETF | ETF와 펀드 차이: 수수료, 거래 방식, 세금을 먼저 비교하기 | ETF vs Mutual Fund: Compare Fees, Trading, and Taxes First | economy decision diagram |
| review | compound-interest-example | CompoundInterest | 복리 계산 예시: 수익률보다 기간과 추가 납입이 중요한 이유 | Compound Interest Example: Time and Contributions Matter | economy decision diagram |
| review | household-budget-50-30-20 | Budgeting | 50/30/20 예산법: 규칙보다 고정비와 현금흐름 먼저 보기 | 50/30/20 Budget Rule: Start With Fixed Costs and Cash Flow | economy decision diagram |
| review | emergency-fund-how-much | EmergencyFund | 비상금은 얼마가 적당할까: 3개월보다 먼저 봐야 할 생활비 | How Much Emergency Fund Is Enough? Start With Essential Costs | economy decision diagram |
| review | recession-indicators-basics | Recession | 경기 침체 지표 읽기: GDP, 고용, 소비를 한 번에 보기 | Recession Indicators: Read GDP, Jobs, and Consumption Together | economy decision diagram |
| review | real-wage-purchasing-power | Wages | 실질임금과 구매력: 월급이 올랐는데 왜 빠듯한지 계산하기 | Real Wages and Purchasing Power: Why Raises Can Still Feel Tight | economy decision diagram |
| review | cpi-vs-personal-inflation | CPI | CPI와 개인 물가 차이: 공식 물가와 체감 물가가 다른 이유 | CPI vs Personal Inflation: Why Official Inflation Feels Different | economy decision diagram |
| review | gdp-components-guide | GDP | GDP 구성요소 읽기: 소비, 투자, 정부, 순수출을 나눠 보기 | GDP Components: Read Consumption, Investment, Government, and Net Exports | economy decision diagram |
| review | unemployment-rate-labor-market | LaborMarket | 실업률과 노동시장: 낮은 실업률만 보면 놓치는 신호 | Unemployment Rate and Labor Market Signals Beyond the Headline | economy decision diagram |
| review | central-bank-meeting-how-to-read | CentralBanks | 중앙은행 회의 읽는 법: 결정문, 전망, 기자회견을 분리하기 | How to Read a Central Bank Meeting: Statement, Projections, Press Conference | economy decision diagram |
| review | bond-yield-curve-basics | Bonds | 채권 금리와 수익률 곡선: 장단기 금리가 말하는 경기 기대 | Bond Yields and the Yield Curve: What Short and Long Rates Signal | economy decision diagram |
| review | household-debt-service-ratio | HouseholdDebt | 가계부채 부담 읽기: 대출 잔액보다 월 상환액이 먼저다 | Household Debt Burden: Monthly Payments Matter Before Balances | economy decision diagram |
| review | current-account-trade-balance | TradeBalance | 경상수지와 무역수지: 수출이 좋아도 환율이 흔들릴 수 있는 이유 | Current Account and Trade Balance: Why Exports Do Not Explain Everything | economy decision diagram |
| review | oil-price-import-inflation | OilPrices | 유가와 수입물가: 국제유가가 전기요금과 장바구니까지 오는 경로 | Oil Prices and Import Inflation: From Crude Markets to Household Bills | economy decision diagram |
| review | semiconductor-cycle-korea-economy | Semiconductors | 반도체 경기와 한국 경제: 수출 호황이 모두에게 같지 않은 이유 | Semiconductor Cycle and Korea: Why Export Booms Feel Uneven | economy decision diagram |
| review | fiscal-deficit-public-debt | FiscalPolicy | 재정적자와 국가채무: 좋은 지출과 지속가능성을 같이 보기 | Fiscal Deficits and Public Debt: Read Support and Sustainability Together | economy decision diagram |
| review | dollar-won-exchange-rate-checklist | KoreanWon | 원달러 환율 체크리스트: 뉴스 한 줄보다 금리차, 유가, 수지를 같이 보기 | Dollar-Won Exchange Rate Checklist: Rates, Oil, and External Balance | economy decision diagram |
| review | savings-rate-real-interest-rate | Saving | 저축금리와 실질금리: 예금 이자가 물가를 이기는지 확인하기 | Savings Rates and Real Interest: Check Whether Interest Beats Inflation | economy decision diagram |
| review | mortgage-rate-rent-affordability | Housing | 주택담보대출 금리와 임대료: 집값보다 월 부담액 먼저 계산하기 | Mortgage Rates and Rent Affordability: Calculate Monthly Burden First | economy decision diagram |
| review | credit-card-interest-minimum-payment | CreditCards | 신용카드 이자와 최소결제: 잔액이 오래 남는 구조 이해하기 | Credit Card Interest and Minimum Payments: Why Balances Last | economy decision diagram |
| review | supply-chain-shock-inflation | SupplyChains | 공급망 충격과 물가: 운임, 재고, 대체 공급처를 같이 보기 | Supply Chain Shocks and Inflation: Freight, Inventories, and Substitutes | economy decision diagram |
| review | productivity-wage-growth | Productivity | 생산성과 임금: 경제가 좋아져도 임금이 늦게 움직이는 이유 | Productivity and Wages: Why Pay Can Lag a Better Economy | economy decision diagram |
| review | inflation-expectations-guide | InflationExpectations | 기대 인플레이션 읽기: 사람들이 믿는 물가가 실제 물가에 미치는 영향 | Inflation Expectations: Why Beliefs About Prices Matter | economy decision diagram |
| review | global-growth-forecast-how-to-read | GlobalEconomy | 세계 성장률 전망 읽기: IMF·OECD·World Bank 숫자가 다른 이유 | How to Read Global Growth Forecasts from IMF, OECD, and World Bank | economy decision diagram |
| review | trade-tariff-household-prices | Tariffs | 관세와 생활물가: 무역정책이 소비자 가격으로 오는 경로 | Tariffs and Household Prices: How Trade Policy Reaches Consumers | economy decision diagram |
| review | emergency-budget-job-loss | EmergencyBudget | 실직 대비 비상 예산: 평상시 예산과 위기 예산을 나누기 | Emergency Budget for Job Loss: Separate Normal and Crisis Spending | economy decision diagram |
| review | deposit-insurance-bank-risk | DepositInsurance | 예금자보호와 은행 리스크: 금리보다 안전 한도를 먼저 확인하기 | Deposit Insurance and Bank Risk: Check Safety Limits Before Yield | economy decision diagram |
| review | consumer-sentiment-economic-signal | ConsumerSentiment | 소비심리 지표 읽기: 기분과 실제 소비를 구분하기 | Consumer Sentiment as an Economic Signal: Separate Mood from Spending | economy decision diagram |
| review | core-vs-headline-inflation | Inflation | 근원물가와 헤드라인 물가: 에너지·식품 변동을 따로 보는 이유 | Core vs Headline Inflation: Why Food and Energy Are Read Separately | economy decision diagram |
| review | nominal-vs-real-gdp | GDP | 명목 GDP와 실질 GDP: 성장과 물가 효과를 분리하기 | Nominal vs Real GDP: Separate Growth from Price Effects | economy decision diagram |
| review | household-balance-sheet-basics | HouseholdFinance | 가계 재무상태표: 소득보다 자산, 부채, 유동성을 함께 보기 | Household Balance Sheet Basics: Assets, Debt, and Liquidity | economy decision diagram |
| review | small-business-break-even-inflation | SmallBusiness | 소상공인 손익분기점과 물가: 매출보다 마진을 먼저 지키기 | Small Business Break-Even and Inflation: Protect Margin Before Revenue | economy decision diagram |
| review | global-dollar-liquidity-basics | Dollar | 달러 유동성 기초: 미국 금리가 세계 금융여건에 미치는 영향 | Global Dollar Liquidity: How U.S. Rates Shape Financial Conditions | economy decision diagram |
| review | economic-calendar-for-households | EconomicCalendar | 가계를 위한 경제 캘린더: CPI, 고용, 금리, 환율 발표일 정리 | Economic Calendar for Households: CPI, Jobs, Rates, and Exchange Rates | economy decision diagram |
Production source for the 2026 expansion: tools/generate_easy_labeling_posts.py.
The three 2025 product introduction and guide pairs are preserved as foundational Easy Labeling articles, while the 2026 campaign expands the field into dataset QA, YOLO formatting, conversion, splitting, review, active learning, privacy, and training handoff.
| Status | Translation ID | Primary keyword | Korean title direction | English title direction | Image direction |
|---|---|---|---|---|---|
| review | easy-labeling-development | Easy Labeling | YOLO 데이터 라벨링, 설치 없이 웹에서 바로! Easy Labeling 개발기 | Introducing Easy Labeling: A Free Web-Based Tool for YOLO Object Detection | product introduction screenshot |
| review | easy-labeling-in-depth-features | Easy Labeling features | YOLO 라벨링 끝판왕, Easy Labeling 주요 기능 파헤치기 | A Deep Dive into Easy Labeling’s Features for YOLO Data Labeling | product feature screenshots |
| review | easy-labeling-guide-1 | Easy Labeling guide | Easy Labeling 가이드 (1) - 이미지와 라벨 불러오기 | Easy Labeling Guide (1) - Loading Images and Labels | product walkthrough screenshots |
| review | yolo-label-format | YOLO | YOLO Label Format 읽는 법: class, center x, center y, width, height 이해하기 | YOLO Label Format: Read Class, Center X, Center Y, Width, and Height | labeling QA diagram |
| review | coco-to-yolo-conversion | COCO | COCO to YOLO 변환 실수: 객체 탐지 라벨이 깨지는 이유 | COCO to YOLO Conversion Mistakes: Avoid Broken Detection Labels | labeling QA diagram |
| review | image-labeling-classes | Classes | 이미지 라벨링 클래스 관리법: class name, ID, dataset consistency 지키기 | Image Labeling Classes: Manage Names, IDs, and Dataset Consistency | labeling QA diagram |
| review | local-image-labeling-workflow | LocalFirst | 로컬 이미지 라벨링 워크플로우: 이미지, 클래스, 라벨, 검수 정리법 | Local Image Labeling Workflow: Organize Images, Classes, Labels, and Review | labeling QA diagram |
| review | easy-labeling-yolo-dataset | EasyLabeling | Easy Labeling으로 YOLO 데이터셋 만들기: 이미지에서 학습 폴더까지 | Build a YOLO Dataset with Easy Labeling: From Images to Training Folders | labeling QA diagram |
| review | bounding-box-quality-checklist | BoundingBox | Bounding Box 품질 체크리스트: 느슨한 박스와 잘린 객체를 줄이는 법 | Bounding Box Quality Checklist: Reduce Loose Boxes and Cut Objects | labeling QA diagram |
| review | labeling-instructions-template | Instructions | 라벨링 지침서 템플릿: 라벨러가 같은 기준으로 박스를 그리게 만드는 법 | Labeling Instructions Template: Make Labelers Draw Boxes the Same Way | labeling QA diagram |
| review | dataset-split-train-val-test | DatasetSplit | Train, Val, Test 데이터셋 분할: 이미지 라벨링 후 누수를 막는 기준 | Train, Val, Test Dataset Split: Prevent Leakage After Image Labeling | labeling QA diagram |
| review | data-yaml-for-yolo | YOLO | YOLO data.yaml 작성법: 경로, 클래스 순서, 검증 오류 줄이기 | YOLO data.yaml Guide: Paths, Class Order, and Validation Errors | labeling QA diagram |
| review | annotation-review-sampling | Review | 라벨 검수 샘플링: 모든 이미지를 다시 보지 않고 품질을 잡는 법 | Annotation Review Sampling: Catch Quality Issues Without Rechecking Everything | labeling QA diagram |
| review | small-object-labeling | SmallObjects | 작은 객체 라벨링 기준: 보이는 물체와 학습 가능한 물체를 구분하기 | Small Object Labeling Rules: Separate Visible Objects from Learnable Objects | labeling QA diagram |
| review | occlusion-truncation-labeling | Occlusion | 가림과 잘림 객체 라벨링: occlusion, truncation 기준을 문서화하기 | Occlusion and Truncation Labeling: Document Edge-Case Rules | labeling QA diagram |
| review | negative-images-for-detection | NegativeSamples | 객체가 없는 이미지도 필요한 이유: YOLO negative sample 설계 | Why Object Detection Needs Negative Images: Design YOLO Negative Samples | labeling QA diagram |
| review | duplicate-image-cleanup | Duplicates | 중복 이미지 정리: 라벨링 전에 near-duplicate를 줄여야 하는 이유 | Duplicate Image Cleanup: Why Near-Duplicates Should Be Reduced Before Labeling | labeling QA diagram |
| review | class-imbalance-dataset | ClassImbalance | 클래스 불균형 데이터셋: 많이 찍힌 클래스만 잘 맞는 문제 줄이기 | Class Imbalance in Datasets: Reduce Models That Only Learn Frequent Classes | labeling QA diagram |
| review | active-learning-labeling-loop | ActiveLearning | Active Learning 라벨링 루프: 모델이 어려워한 이미지부터 다시 라벨링하기 | Active Learning Labeling Loop: Relabel the Images Your Model Finds Hard | labeling QA diagram |
| review | prelabeling-human-review | PreLabeling | Pre-labeling과 사람 검수: 자동 라벨을 그대로 믿지 않는 워크플로우 | Pre-Labeling and Human Review: Do Not Trust Auto Labels Without QA | labeling QA diagram |
| review | video-frame-extraction-labeling | VideoFrames | 비디오 프레임 라벨링: 너무 많은 비슷한 장면을 줄이는 추출 기준 | Video Frame Labeling: Extract Frames Without Flooding the Dataset | labeling QA diagram |
| review | segmentation-vs-detection-labels | Segmentation | Segmentation과 Detection 라벨 선택: 박스가 충분한지 마스크가 필요한지 판단하기 | Segmentation vs Detection Labels: Decide Whether Boxes Are Enough | labeling QA diagram |
| review | rotated-bounding-box-decision | RotatedBox | Rotated Bounding Box가 필요한 경우: 기울어진 객체를 일반 박스로 충분히 표현할 수 있을까 | When Rotated Bounding Boxes Matter: Are Regular Boxes Enough? | labeling QA diagram |
| review | label-version-control | VersionControl | 라벨 버전 관리: 데이터셋 v1, v2를 되돌릴 수 있게 만드는 방법 | Label Version Control: Make Dataset v1 and v2 Reversible | labeling QA diagram |
| review | dataset-folder-structure | FolderStructure | 객체 탐지 데이터셋 폴더 구조: images와 labels를 안전하게 맞추기 | Object Detection Dataset Folder Structure: Keep Images and Labels Aligned | labeling QA diagram |
| review | model-error-analysis-labeling | ErrorAnalysis | 모델 오류 분석으로 라벨링 개선하기: 오탐과 미탐을 다음 작업으로 바꾸기 | Improve Labeling with Model Error Analysis: Turn FP and FN into Next Work | labeling QA diagram |
| review | annotation-cost-estimation | AnnotationCost | 이미지 라벨링 비용 산정: 장당 시간이 아니라 재작업률까지 계산하기 | Annotation Cost Estimation: Count Rework, Not Only Time Per Image | labeling QA diagram |
| review | privacy-local-labeling | Privacy | 민감한 이미지 라벨링과 로컬 우선 작업: 업로드 전에 확인할 보안 기준 | Sensitive Image Labeling and Local-First Work: Security Checks Before Uploads | labeling QA diagram |
| review | augmentation-label-safety | Augmentation | 데이터 증강 전 라벨 안전성: 회전, 자르기, 뒤집기가 박스를 망가뜨리지 않게 하기 | Label Safety Before Data Augmentation: Keep Boxes Valid After Crop and Flip | labeling QA diagram |
| review | exporting-yolo-training-ready | Export | YOLO 학습 준비 export 체크리스트: 라벨링 끝난 뒤 바로 훈련하지 말아야 하는 이유 | YOLO Training-Ready Export Checklist: Do Not Train Immediately After Labeling | labeling QA diagram |
| review | label-format-migration-plan | FormatMigration | 라벨 포맷 전환 계획: YOLO, COCO, CVAT 사이를 오갈 때 지킬 기준 | Label Format Migration Plan: Move Between YOLO, COCO, and CVAT Safely | labeling QA diagram |
| review | edge-case-gallery-dataset | EdgeCases | Edge Case Gallery 만들기: 애매한 라벨 기준을 이미지로 고정하는 법 | Build an Edge Case Gallery: Freeze Ambiguous Label Rules with Images | labeling QA diagram |
| review | qa-before-yolo-training | QA | YOLO 학습 전 QA 루틴: 데이터 오류를 모델 문제로 착각하지 않기 | QA Before YOLO Training: Do Not Mistake Data Errors for Model Problems | labeling QA diagram |
| review | labeler-onboarding-checklist | Onboarding | 라벨러 온보딩 체크리스트: 첫날부터 같은 기준으로 작업하게 만들기 | Labeler Onboarding Checklist: Start New Annotators with the Same Standard | labeling QA diagram |
| review | dataset-handoff-for-training | Handoff | 라벨링 팀에서 학습 팀으로 데이터 넘기기: handoff 문서에 들어갈 것 | Dataset Handoff for Training Teams: What to Include in the Handoff Document | labeling QA diagram |
| review | browser-based-labeling-pros-cons | BrowserTool | 브라우저 기반 라벨링 도구 장단점: 설치 없음과 파일 접근 권한 사이의 균형 | Browser-Based Labeling Tools: Balance No Install with File Access Control | labeling QA diagram |
| review | image-labeling-project-plan | ProjectPlan | 이미지 라벨링 프로젝트 계획서: 수집, 라벨링, 검수, 학습을 한 흐름으로 묶기 | Image Labeling Project Plan: Connect Collection, Annotation, QA, and Training | labeling QA diagram |
For each topic pair:
images/YYYY-MM-DD-slug/.hero.png, workflow.png, or example-output.png._includes/head/custom.html.ads.txt: pub-2983974324971673._includes/ad-content.html and _includes/ad-inarticle.html.adsense.in_article_slot and adsense.post_bottom_slot are set.