# GYee/CV_interviews_Q-A

CV算法岗知识点及面试问答汇总，主要分为计算机视觉、机器学习、图像处理和 C++基础四大块，一起努力向offers发起冲击！

Repository: https://github.com/GYee/CV_interviews_Q-A
Canonical: https://ross.abutalabs.com/products/cv_interviews_q-a
License Family: other
Last push: 2021-11-02T01:25:43+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2299, "days_push": 1766, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1802, forks 268 (observed 2026-08-28T04:05:38.153768+00:00)

## What it is
A curated Chinese-language collection of computer vision algorithm engineer interview questions and answers, organized into computer vision, machine learning, image processing, and C++ fundamentals. It provides detailed explanations of core concepts like convolution, batch normalization, NMS, backpropagation, and optimization.

## Use cases
- prepare for computer vision algorithm engineer interviews
- review deep learning fundamentals like BN layers and backpropagation
- study common CV interview questions with detailed answers
- brush up on image processing and C++ basics before job interviews
- find a structured question bank for ML/CV job hunting

## When to choose
- you are preparing for a CV/ML algorithm role interview and want curated Q&A in Chinese
- you want concise explanations of classic deep learning and image processing interview topics
- you prefer markdown or PDF study notes over video courses

## When to avoid
- you need up-to-date content on modern architectures like transformers or diffusion models, as the repo was last updated in 2021
- you need English-language study material
- you want hands-on code projects rather than conceptual Q&A notes

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: computer-vision, machine-learning, deep-learning, tutorials, education
- platform: cross-platform
- tags: interview-preparation, computer-vision, machine-learning, image-processing, cpp, question-bank, chinese-language

## Member repositories
- GYee/CV_interviews_Q-A (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:38.153768+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:21:53.623560+00:00, confidence not recorded.
  - readme: https://github.com/GYee/CV_interviews_Q-A (fetched 2026-08-28T04:05:38.153768+00:00, sha 40c11170aca6)
- Data as of 2026-08-30T08:39:29.467469+00:00.