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AI/Stanford CS231n2

Lecture 2. Image Classification Image Classification What is Image Classification? Example : Input : ๊ณ ์–‘์ด ์‚ฌ์ง„ ์ปดํ“จํ„ฐ๋Š” ์‚ฌ์ „์— ์ •ํ•ด์ง„ label๋“ค์˜ ์ง‘ํ•ฉ์„(predetermined set of labels) ๊ฐ€์ง€๊ณ , input๊ฐ’๊ณผ ์ผ์น˜ํ•˜๋Š” label๊ฐ’์„ output์œผ๋กœ ์ถœ๋ ฅํ•˜๋„๋ก ๊ณ„์‚ฐํ•œ๋‹ค. Output : Cat Semantic Gap (์˜๋ฏธ์  ์ฐจ์ด) ์ •์˜ : ์‹ค์ œ ์ด๋ฏธ์ง€๊ฐ€ ๊ฐ–๊ณ  ์žˆ๋Š” ์˜๋ฏธ์™€ ์ปดํ“จํ„ฐ๊ฐ€ ๋ณด๋Š” ํ”ฝ์…€๊ฐ’ ์˜๋ฏธ์˜ ์ฐจ์ด ์šฐ๋ฆฌ๋Š” ์‰ฝ๊ฒŒ ๊ณ ์–‘์ด๋ฅผ ๋ณด๊ณ  "๊ณ ์–‘์ด"์ž„์„ ๋ถ„๋ฅ˜ํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ์ปดํ“จํ„ฐ์˜ ๊ฒฝ์šฐ์—๋Š” ํ•˜๋‚˜์˜ image๊ฐ€ ๊ฑฐ๋Œ€ํ•œ ์ˆซ์ž ๊ทธ๋ฆฌ๋“œ(gigantic grid of numbers)๋กœ ๋ณด์ด๊ธฐ ๋•Œ๋ฌธ์— ๊ณ ์–‘์ด๋ฅผ ๋ฐ”๋กœ ์—ฐ์ƒํ•  ์ˆ˜ ์—†๋Š” ๊ฒƒ์ด๋‹ค. Challenges : Viewpoin.. 2024. 2. 16.
Lecture 13. Generative Models Overview - Unsupervised Learning - Generative Models PixelRNN and PixelCNN Variational Autoencoders (VAE) Generative Adversarial Networks (GAN) Classification : Input : Image Output : Text (Label) Object Detection : Input : Image Output : Bounding Boxes of instances Semantic Segmentation (having label for every pixel) : ? Image Captioning : Input : Image Output : Caption (form of natural languag.. 2024. 2. 13.

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