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Lecture 1: Deep Learning for Computer Vision
This document discusses how deep learning has helped advance computer vision capabilities. It notes that deep learning can help bridge the gap between pixels and meaning by allowing computers to recognize complex patterns in images. It provides an overview of related fields like image processing, machine learning, artificial intelligence, and computer graphics. It also lists some specific applications of deep learning like object detection, image classification, and generating descriptive text. Students are then assigned a task to research how deep learning has improved one particular topic and submit a two-page summary.
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Lecture 1: Deep Learning for Computer Vision
- 1. Deep Learning forComputer Vision
- 2. To bridgethe gap between pixels and “meaning” What we see What a computer sees
- 3. Computer Vision Image Processing MachineLearning Artificial Intelligence Robotics Deep Learning Computer Graphics
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- 5. Vehicle wheel Animal leg head Four-legged Mammal Move onroad Facing right Can run, jump Is herbivorous Facing right
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- 16. How many bikesare there? 2 What the number is the bus? 48
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- 25. Directional strokeerror of character Seen.
- 28. Deep Learningnot only used for computer vision Deep Learning for Natural Language Processing Deep Learning for Speech Processing Deep Learning for Robotics Deep Learning for Art Deep Learning for Data mining Deep Learning for Games
- 29. Artificial Neural Network Convolutional Neural Networks How itWorks: CNN Deep Learning Frameworks Convolutional Neural Network Models Deep Learning Architectures
- 30. Each student selectone topic from slides. Search how deep learning has greatly advanced the performance of this topic. Make two pages using word to summarize your search. Don’t forget to put references (new references at least 5 years ago).
- 31. Use MS Word Sendme e-mail to mloey@live.com with email subject “ Advanced Topics in CS2 – Task1 “ Put your Arabic name on word and email body Finally, press Send Deadline Next Lecture
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