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Study-PaperReview

๐Ÿงย ๋Œ€์ƒ

  • ์ธ๊ณต์ง€๋Šฅ ๋…ผ๋ฌธ์„ ๊พธ์ค€ํžˆ ์ฝ๊ณ  ์‹ถ์€ ๋ถ„
  • ๋…ผ๋ฌธ ์ฝ๊ธฐ ๋ฐ ๊ตฌํ˜„์ด ์ฒ˜์Œ์ด์‹  ๋ถ„๋„ ์™„์ „ ํ™˜์˜์ž…๋‹ˆ๋‹ค !

๐Ÿ“†ย ๊ธฐ๊ฐ„

  • 4์›” 4์ผ~ 3-2๊ธฐ closing session ์ „ ์ฃผ

    ์ดํ›„ ํ™œ๋™ ์—ฌ๋ถ€๋Š” ์˜๋…ผํ•ด๋ด์š” :>

๐Ÿ”–ย ๋ฐฉ์‹

  • ๋ณธ์ธ์ด ์—ฐ๊ตฌํ•˜๊ณ  ์žˆ๋Š” ๋ถ„์•ผ/๊ด€์‹ฌ ๋ถ„์•ผ์˜ ๋…ผ๋ฌธ์„ ์ผ์ฃผ์ผ์— 1ํŽธ์”ฉ ์ฝ๊ณ  โ€˜ํ•ต์‹ฌ๋งŒโ€™ ์š”์•ฝํ•˜์—ฌ ์—…๋กœ๋“œํ•ฉ๋‹ˆ๋‹ค.

    ์‹œํ—˜ ๊ธฐ๊ฐ„์€ ์ถ”ํ›„ ์Šคํ„ฐ๋””์›๋“ค์˜ ์˜๊ฒฌ์— ๋”ฐ๋ผ ํœด์‹ ์—ฌ๋ถ€ ๊ฒฐ์ •

  • ๊นƒํ—ˆ๋ธŒ๋ฅผ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค.

    1. Issue ํƒญ์— ์—…๋กœ๋“œ

      • Issue Title: ์ฝ์€ ๋…ผ๋ฌธ์˜ ์ œ๋ชฉ
      • Comment: ๋…ผ๋ฌธ ์š”์•ฝ (ํ˜•์‹์€ ์ž์œ )
      • Labels: Mandatory ์ด๋ฆ„, ๋…ผ๋ฌธ ๋ถ„์•ผ Optional ๋ฐœํ–‰์—ฐ๋„, ์ปจํผ๋Ÿฐ์Šค๋ช…(e.g., CVPR, ICCV...)
    2. ์›”๋ณ„ md ํŒŒ์ผ์— ์ฝ์€ ๋…ผ๋ฌธ ์›๋ณธ ์—…๋กœ๋“œ

    3. ๋‹ค๋ฅธ ์Šคํ„ฐ๋””์›๋“ค์ด ์˜ฌ๋ฆฐ ๋…ผ๋ฌธ์€ ๋‹ค์Œ ์ฃผ์ฐจ ๋…ผ๋ฌธ ์—…๋กœ๋“œ ์ „๋‚ ๊นŒ์ง€ ํ™•์ธ ํ›„, Comment ๋‚จ๊ธฐ๊ธฐ

      ๊ฐ„๋‹จํ•œ ์ฝ”๋ฉ˜ํŠธ๋„ ๊ดœ์ฐฎ์Šต๋‹ˆ๋‹ค. ๋ถ€๋‹ด ์—†์ด ๋‚จ๊ฒจ์ฃผ์‹œ๋ฉด ๋ฉ๋‹ˆ๋‹ค :> (์ž˜ ์ฝ์—ˆ์Šต๋‹ˆ๋‹ค~, ์ด๋Ÿฐ ๋…ผ๋ฌธ๋„ ๋‹ค์Œ์— ์ฝ์–ด๋ณด์„ธ์š” ๋“ฑ ์–ด๋– ํ•œ ์ฝ”๋ฉ˜ํŠธ ๋‹ค ๊ฐ€๋Šฅ ! )

  • Optional

    โ€˜๋‚˜๋Š” ์ข€ ๋” ์ž์„ธํžˆ ๊ธฐ๋กํ•ด๋‘๊ณ  ์‹ถ๋‹คโ€™ ๋Š” ๋ถ„๋“ค์„ ์œ„ํ•œ ์„ ํƒ ์‚ฌํ•ญ์ž…๋‹ˆ๋‹ค.

    • ๋…ธ์…˜, ํ‹ฐ์Šคํ† ๋ฆฌ, ๋ฒจ๋กœ๊ทธ ๋“ฑ ์ž์‹ ์ด ์ฝ์€ ๋…ผ๋ฌธ ๋‚ด์šฉ์„ ์ž์„ธํ•˜๊ฒŒ ๊ธฐ๋ก
    • ๋งํฌ๋ฅผ ReadMe ์— ์˜ฌ๋ฆฐ ๋…ผ๋ฌธ ์›๋ณธ ์˜†์— ๊ฐ™์ด ์—…๋กœ๋“œ

๐Ÿ“ย ๊ทœ์น™

  • ์—…๋กœ๋“œ๋Š” ๋งค์ฃผ ์›”์š”์ผ ์ž์ • ์ „๊นŒ์ง€

    (21์ผ ์‹œ์ž‘ ๊ธฐ์ค€ โ†’ 27์ผ 23์‹œ 59๋ถ„ 59์ดˆ๊นŒ์ง€)

  • ์ฝ”๋ฉ˜ํŠธ๋Š” ์—…๋กœ๋“œ ํ•œ ๋‹ค์Œ์ฃผ ์ผ์š”์ผ ์ž์ • ์ „๊นŒ์ง€

    (21์ผ ์‹œ์ž‘ ๊ธฐ์ค€ โ†’ 4์›” 3์ผ 23์‹œ 59๋ถ„ 59์ดˆ๊นŒ์ง€)

  • ๋ฒŒ๊ธˆ๐Ÿ’ธ โ†’ ์ง€๊ฐ: 2000์›/ ๊ฒฐ์„: 3000์›/ ๋Šฆ์€ ๊ณต์ง€: 1000์›/ ์ฝ”๋ฉ˜ํŠธ ๋ฏธ์—…๋กœ๋“œ: 1000์›

    ๋‹ค์Œ๋‚  ๋‚ฎ 12์‹œ๊นŒ์ง€ ๋ฏธ์—…๋กœ๋“œ = ๊ฒฐ์„

    ๊ณผ์ œ ์ œ์ถœ ์—ฌ๋ถ€์™€ ๊ด€๊ณ„์—†์ด ์ฝ”๋ฉ˜ํŠธ ๋ฏธ์—…๋กœ๋“œ ์‹œ ๋ฒŒ๊ธˆ ๋ถ€๊ณผ

    ๋ฒŒ๊ธˆ ์ •์‚ฐ์€ ํ•œ ๋‹ฌ์— ํ•œ ๋ฒˆ โ†’ ์ •์‚ฐ์€ ์Šคํ„ฐ๋”” ์ข…๋ฃŒ ํ›„ ํ•œ๋ฒˆ์— ์ž…๊ธˆ ๋ฐ›๊ณ  ์ •์‚ฐ ํ•˜๊ฒ ์Šต๋‹ˆ๋‹ค!(ํ†ต์žฅ ๊ฐœ์„ค์— ์ œํ•œ์ด ์žˆ์–ด์„œ๐Ÿ˜ข)

    ๊ผด์ฐŒ ์ œ์™ธ 1/n (์ฐธ์—ฌํ•˜๋Š” ์ธ์›์— ๋”ฐ๋ผ ๋ฐ”๋€” ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค)

๐Ÿ‘€ย ๊ทธ ์™ธ

  • ์ด์Šˆ ํƒญ์€ ์Šคํ„ฐ๋””์žฅ์ด ๋งค์ฃผ ์›”์š”์ผ ์ž์ • ์ „์— Close ํ•ฉ๋‹ˆ๋‹ค.

  • ๋ถ€๋‹ด ์—†์ด ๋…ผ๋ฌธ์„ ์ฝ๋Š” ์Šคํ„ฐ๋””์ธ ๋งŒํผ ํ•œ ๋‹ฌ์— ํ•œ ๋ฒˆ ํœด์‹ ๊ฐ€๋Šฅ ํ•ฉ๋‹ˆ๋‹ค.

    ๋Œ€์‹  ์—…๋กœ๋“œ ์ „ ์ฃผ์— ๊ผญ ์‚ฌ์ „๊ณต์ง€ ํ•ด์ฃผ์„ธ์š” ! ๋Šฆ์€ ๊ณต์ง€๋Š” ๋ฒŒ๊ธˆ์ด...๐Ÿฅฒ

    (28์ผ์— ํœด์‹ํ•˜๊ณ  ์‹ถ๋‹ค โ†’ 21์ผ 23์‹œ 59๋ถ„ 59์ดˆ๊นŒ์ง€ ๊ณต์ง€)

  • ํŒ€๋ธ”๋กœ๊ทธ ํฌ์ŠคํŒ…์€ ๋Œ์•„๊ฐ€๋ฉด์„œ ํ•ฉ๋‹ˆ๋‹ค.

  • ์Šคํ„ฐ๋”” ๋ฐฉ์‹, ๊ทœ์น™์— ๋Œ€ํ•œ ์˜๊ฒฌ์ด ์žˆ๋‹ค๋ฉด, ์–ธ์ œ๋“ ์ง€ ๊ณต์œ ํ•ด์ฃผ์„ธ์š” :>

๐Ÿ“šย ์ฐธ๊ณ 

[๋…ผ๋ฌธ ์–ด๋””์„œ ์ฝ์ง€?]

Papers You Must Read (PYMR)

Papers with Code - The most popular papers with code

GitHub - hurshd0/must-read-papers-for-ml: Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer

GitHub - floodsung/Deep-Learning-Papers-Reading-Roadmap: Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

AI ๋…ผ๋ฌธ ์‚ฌ์ดํŠธ ๋ชจ์Œ (feat. ํ˜„์—… ์ด์Šˆ)

[๋…ผ๋ฌธ ์–ด๋–ป๊ฒŒ ์ฝ์–ด์•ผ ํ•˜์ง€?]

media-ai

[๋Œ€ํ•™์› ๊ฟ€ํŒ] ๋…ผ๋ฌธ ์ฝ๋Š” ๋ฒ•(feat. ๋…ผ๋ฌธ ๋ฆฌ๋ทฐ ๋ฐฉ๋ฒ•)