딥 러닝 전문화의 네 번째 과정에서는 컴퓨터 비전이 어떻게 발전해 왔는지 이해하고 자율 주행, 얼굴 인식, 방사선 이미지 읽기 등과 같은 흥미로운 애플리케이션에 익숙해질 것입니다.
Expérience recommandée
Compétences que vous acquerrez
- Catégorie : Facial Recognition System
- Catégorie : Artificial Neural Network
- Catégorie : Automatic Image Annotation
- Catégorie : Vision Objects
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Il y a 4 modules dans ce cours
CNN의 기본 레이어(풀링, 컨볼루션)를 구현하고 심층 네트워크에 적절하게 스택하여 다중 클래스 이미지 분류 문제를 해결합니다.
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12 vidéos6 lectures1 devoir2 devoirs de programmation2 éléments d'application
연구 논문을 통해 Deep CNN에서 사용되는 강력하고 실용적인 트릭과 방법을 바로 확인하고 전이 학습을 자신의 Deep CNN에 적용하십시오.
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14 vidéos1 lecture1 devoir2 devoirs de programmation1 élément d'application
CNN에 대한 새로운 지식을 컴퓨터 시각 인식에서 가장 인기 있고 가장 도전적인 분야 중 하나인 객체 감지에 적용합니다.
Inclus
14 vidéos3 lectures1 devoir2 devoirs de programmation1 élément d'application
아트 작품 생성 및 얼굴 인식을 포함한 여러 분야에 CNN을 적용할 수 있는 방법을 살펴보고 나만의 알고리즘을 구현하여 아트 작품을 생성하고 얼굴을 인식할 수 있습니다!
Inclus
11 vidéos5 lectures1 devoir2 devoirs de programmation1 élément d'application
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DeepLearning.AI
DeepLearning.AI
Macquarie University
DeepLearning.AI
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