このコースについて

82,087 最近の表示
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における7の5コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
上級レベル
約13時間で修了
英語
字幕:英語, 韓国語
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における7の5コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
上級レベル
約13時間で修了
英語
字幕:英語, 韓国語

提供:

ロシア国立研究大学経済高等学院(National Research University Higher School of Economics) ロゴ

ロシア国立研究大学経済高等学院(National Research University Higher School of Economics)

シラバス - 本コースの学習内容

コンテンツの評価Thumbs Up83%(1,027 件の評価)Info
1

1

3時間で修了

Introduction to image processing and computer vision

3時間で修了
9件のビデオ (合計56分), 1 reading, 2 quizzes
9件のビデオ
Short introduction to computer vision4 分
Digital images3 分
Structure of human eye and vision6 分
Color models15 分
Image processing goals and tasks2 分
Contrast and brightness correction5 分
Image convolution7 分
Edge detection8 分
1件の学習用教材
About the University10 分
1の練習問題
Basic image processing30 分
2

2

3時間で修了

Convolutional features for visual recognition

3時間で修了
12件のビデオ (合計91分)
12件のビデオ
AlexNet, VGG and Inception architectures11 分
ResNet and beyond10 分
Fine-grained image recognition5 分
Detection and classification of facial attributes6 分
Content-based image retrieval7 分
Computing semantic image embeddings using convolutional neural networks8 分
Employing indexing structures for efficient retrieval of semantic neighbors9 分
Face verification6 分
The re-identification problem in computer vision5 分
Facial keypoints regression6 分
CNN for keypoints regression5 分
1の練習問題
Convolutional features for visual recognition30 分
3

3

2時間で修了

Object detection

2時間で修了
13件のビデオ (合計46分)
13件のビデオ
Sliding windows3 分
HOG-based detector2 分
Detector training3 分
Viola-Jones face detector5 分
Attentional cascades and neural networks3 分
Region-based convolutional neural network3 分
From R-CNN to Fast R-CNN5 分
Faster R-CNN4 分
Region-based fully-convolutional network2 分
Single shot detectors3 分
Speed vs. accuracy tradeoff1 分
Fun with pedestrian detectors1 分
1の練習問題
Object Detection30 分
4

4

3時間で修了

Object tracking and action recognition

3時間で修了
11件のビデオ (合計74分)
11件のビデオ
Optical flow5 分
Deep learning in optical flow estimation5 分
Visual object tracking5 分
Examples of visual object tracking methods13 分
Multiple object tracking5 分
Examples of multiple object tracking methods8 分
Introduction to action recognition6 分
Action classification7 分
Action classification with convolutional neural networks5 分
Action localization6 分
1の練習問題
Video Analysis30 分

レビュー

DEEP LEARNING IN COMPUTER VISION からの人気レビュー

すべてのレビューを見る

上級機械学習専門講座について

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings....
上級機械学習

よくある質問

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。