๋๋น๋
|
๋น์ ๊ณต์๋ฅผ ์ํ ์ดํดํ ์ ์๋ ํ์ด์ฌ: 1์๊ฐ 30๋ถ์ผ๋ก ํ์ด์ฌ ๋๋ด๊ธฐ
|
08-31 22:07:29
|
09-30 21:05:26
|
x
|
๋๋น๋
|
๋ฅ๋ฌ๋ ์ ์ด ํ์ต(Transfer Learning) ์๋ฒฝ ์ดํด: BiT ๋
ผ๋ฌธ ์ค๋ช
(ECCV 2020)
|
03-25 23:50:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
IT ๊ฐ๋ฐ ํ์ฌ ์ค์ ๋ฉด์ Tip ๋๋ฐฉ์ถ: ๋น์ ๊ณต์ ๊ฐ์ ๋ฉด์ (Feat. SW๋ง์์คํธ๋ก)
|
01-14 21:15:02
|
05-16 23:31:00
|
x
|
๋๋น๋
|
๋ฐฐ์น ์ ๊ทํ(Batch Normalization) [๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต]
|
01-14 13:45:02
|
05-16 23:31:00
|
x
|
๋๋น๋
|
GAN: Generative Adversarial Networks (๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต)
|
12-23 07:30:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๋ฅ๋ฌ๋ ๊ธฐ๊ณ ๋ฒ์ญ] Transformer: Attention Is All You Need (๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต)
|
12-13 15:49:24
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[ํ
์คํธ ๋ถ๋ฅ ๋ชจ๋ธ ๊ณต๊ฒฉ ๊ธฐ๋ฒ] TextFooler: Is BERT Really Robust?
|
11-23 07:07:32
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๋ฅ๋ฌ๋ ๊ธฐ๊ณ ๋ฒ์ญ] Seq2Seq: Sequence to Sequence Learning with Neural Networks (๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต)
|
11-13 07:30:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ฝ๋ฉ ํ
์คํธ๋ฅผ ์ํ ํธ๋ฆฌ(Tree) ์๋ฃ๊ตฌ์กฐ 10๋ถ ํต์ฌ ์์ฝ
|
11-08 17:00:06
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ฝ๋ฉ ํ
์คํธ๋ฅผ ์ํ ๋ฒจ๋ง ํฌ๋ ์๊ณ ๋ฆฌ์ฆ 7๋ถ ํต์ฌ ์์ฝ
|
11-07 14:51:49
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์๋ฃ๊ตฌ์กฐ: ๋ฐ์ด๋๋ฆฌ ์ธ๋ฑ์ค ํธ๋ฆฌ(Binary Indexed Tree, BIT, ํ์
ํธ๋ฆฌ) 10๋ถ ์ ๋ณต
|
11-06 20:30:03
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ต์ ๊ณตํต ์กฐ์(Lowest Common Ancestor, LCA) ์๊ณ ๋ฆฌ์ฆ 10๋ถ ์ ๋ณต
|
11-05 20:02:38
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์๋ฃ๊ตฌ์กฐ: ์ฐ์ ์์ ํ(Priority Queue)์ ํ(Heap) 10๋ถ ํต์ฌ ์์ฝ
|
11-04 20:00:02
|
05-16 23:31:00
|
x
|
๋๋น๋
|
ResNet: Deep Residual Learning for Image Recognition (๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต)
|
10-29 10:44:23
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ปดํจํฐ ๊ณตํ๊ณผ๋ฅผ ์ํ ์ต์ ๋
ผ๋ฌธ ์ฐพ์ ์ฝ๋ ๋ฐฉ๋ฒ ์ ๋ฆฌ (์
๋ฌธ์๋ฅผ ์ํ)
|
10-15 20:40:24
|
05-16 23:31:00
|
x
|
๋๋น๋
|
StarGAN (๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต)
|
10-13 09:12:42
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 10. ๊ฐ๋ฐํ ์ฝ๋ฉ ํ
์คํธ
|
10-10 23:07:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 9. ์ฝ๋ฉ ํ
์คํธ์์ ์์ฃผ ์ถ์ ๋๋ ๊ธฐํ ์๊ณ ๋ฆฌ์ฆ
|
10-10 09:30:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 8. ๊ธฐํ ๊ทธ๋ํ ์ด๋ก
|
10-07 12:15:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 7. ์ต๋จ ๊ฒฝ๋ก ์๊ณ ๋ฆฌ์ฆ
|
10-05 18:30:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 6. ๋ค์ด๋๋ฏน ํ๋ก๊ทธ๋๋ฐ
|
10-04 10:00:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 5. ์ด์ง ํ์
|
10-03 09:25:06
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 4. ์ ๋ ฌ ์๊ณ ๋ฆฌ์ฆ
|
10-02 09:00:06
|
05-16 23:31:00
|
x
|
๋๋น๋
|
Meta-Transfer Learning for Zero-Shot Super-Resolution (๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต)
|
09-30 17:23:23
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 3. DFS & BFS
|
09-28 23:40:10
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 2. ๊ทธ๋ฆฌ๋ & ๊ตฌํ
|
09-27 21:19:58
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(์ด์ฝํ
2021 ๊ฐ์ ๋ชฐ์๋ณด๊ธฐ) 1. ์ฝ๋ฉ ํ
์คํธ ์ถ์ ๊ฒฝํฅ ๋ถ์ ๋ฐ ํ์ด์ฌ ๋ฌธ๋ฒ ๋ถ์๊ธฐ
|
09-27 00:52:48
|
05-16 23:31:00
|
x
|
๋๋น๋
|
Shadow Attack - Semantic Adversarial Examples (๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต)
|
09-20 15:31:42
|
05-16 23:31:00
|
x
|
๋๋น๋
|
DETR: End-to-End Object Detection with Transformers (๊ผผ๊ผผํ ๋ฅ๋ฌ๋ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ์ ์ฝ๋ ์ค์ต)
|
09-19 06:19:31
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๊ผผ๊ผผํ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ] Adversarial Patch: ์คํฐ์ปค๋ฅผ ๋ถ์ด๊ธฐ๋ง ํ๋ฉด ์ธ๊ณต์ง๋ฅ์ด ๋ง๊ฐ์ง๋ค! [NIPS 2017] (์ธ๊ณต์ง๋ฅ ๋ณด์/AI Security)
|
07-07 23:49:13
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๊ผผ๊ผผํ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ] Constructing Unrestricted Adversarial Examples with Generative Models [NIPS 2018] (AI๋ณด์)
|
03-30 20:15:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๊ผผ๊ผผํ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ] Obfuscated Gradients Give a False Sense of Security [ICML 2018] (์ธ๊ณต์ง๋ฅ ๋ณด์)
|
03-27 21:30:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๊ผผ๊ผผํ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ] Certified Robustness to Adversarial Examples with Differential Privacy [S&P 2019] (AI๋ณด์)
|
03-19 22:00:18
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๊ผผ๊ผผํ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ] Towards Deep Learning Models Resistant to Adversarial Attacks [ICLR 2018] (์ธ๊ณต์ง๋ฅ ๋ณด์)
|
03-08 21:00:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์์ฐ๋์ e(Euler's number) | ์ธ๊ณต์ง๋ฅ ๋ฐ ์ปดํจํฐ ๋น์ ์ ์ํ ์ํ ํต์ฌ ๊ฐ๋
๋
ธํธ(Mathematics for AI)
|
03-08 16:48:51
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๊ผผ๊ผผํ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ] Adversarial Examples Are Not Bugs, They Are Features [NIPS 2019] (์ธ๊ณต์ง๋ฅ ๋ณด์)
|
03-06 22:31:49
|
05-16 23:31:00
|
x
|
๋๋น๋
|
๋ฏธ๋ถ๊ณผ ํธ๋ฏธ๋ถ(Ordinary Derivative & Partial Derivative) | ์ธ๊ณต์ง๋ฅ ๋ฐ ์ปดํจํฐ ๋น์ ์ ์ํ ์ํ ํต์ฌ ๊ฐ๋
๋
ธํธ(Mathematics for AI)
|
03-01 00:04:58
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๊ผผ๊ผผํ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ] Towards Evaluating the Robustness of Neural Networks [S&P 2017] (์ธ๊ณต์ง๋ฅ ๋ณด์/AI Security)
|
02-28 20:04:04
|
05-16 23:31:00
|
x
|
๋๋น๋
|
๋ณผ๋ก ํจ์(Convex Function) | ์ธ๊ณต์ง๋ฅ ๋ฐ ์ปดํจํฐ ๋น์ ์ ์ํ ์ํ ํต์ฌ ๊ฐ๋
๋
ธํธ(Mathematics for AI)
|
02-26 08:30:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
๋ดํด ๋ฐฉ๋ฒ(Newton Method) | ์ธ๊ณต์ง๋ฅ ๋ฐ ์ปดํจํฐ ๋น์ ์ ์ํ ์ํ ํต์ฌ ๊ฐ๋
๋
ธํธ(Mathematics for AI)
|
02-24 21:00:07
|
05-16 23:31:00
|
x
|
๋๋น๋
|
๋ฅ ํ์ดํฌ(Deepfakes) ์ต์ ์ฐ๊ตฌ ๋ํฅ - ๊ฐ์ง ์์ ์ ์๊ณผ ํ์ง ๊ธฐ์ ์ ๋ฆฌ(Deep Learning for Deepfakes Creation and Detection)
|
02-22 18:01:19
|
05-16 23:31:00
|
x
|
๋๋น๋
|
[๊ผผ๊ผผํ ๋
ผ๋ฌธ ๋ฆฌ๋ทฐ] Explaining and Harnessing Adversarial Examples [ICLR 2015] (์ธ๊ณต์ง๋ฅ ๋ณด์/AI Security)
|
02-19 21:00:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
(๋น์ ๊ณต์) ์ธ๊ณต์ง๋ฅ ๋ถ์ผ ์ต์ ํธ๋ ๋๋ฅผ ๋ฐ๋ผ๊ฐ๋ ๋ฐฉ๋ฒ ๋ฐ ๋
ผ๋ฌธ ์ฝ๊ธฐ ์กฐ์ธ [ ๊ฐ๋ฐ์์ ์ ํ ์๋ด์ ]
|
02-02 09:58:17
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ฝ๋ฉ ํ
์คํธ์์ ๋ฌด์์ ๋ฌผ์ด๋ณด๋์? ์ด๋ค ์ธ์ด๊ฐ ๊ฐ์ฅ ์ ๋ฆฌํ๊ฐ์? [ ๊ฐ๋ฐ์์ ์ ํ ์๋ด์ ]
|
01-18 14:53:11
|
05-16 23:31:00
|
x
|
๋๋น๋
|
๋ค์ด๋ฒ ์ํ ๋ฆฌ๋ทฐ ๋ฐ์ดํฐ ๋ถ์ โก ๋ฐ์ดํฐ ์๊ฐํ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
|
10-04 20:00:08
|
05-16 23:31:00
|
x
|
๋๋น๋
|
๋ค์ด๋ฒ ์ํ ๋ฆฌ๋ทฐ ๋ฐ์ดํฐ ๋ถ์ โ ์ํ ์ ๋ณด ํฌ๋กค๋ง [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
|
10-04 19:30:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์น ํฌ๋กค๋ง [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ] (Web Crawling)
|
10-04 19:00:10
|
05-16 23:31:00
|
x
|
๋๋น๋
|
Matplotlib ๋ค๋ฃจ๊ธฐ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
|
10-03 23:45:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
Matplotlib์ ๊ธฐ์ด [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
|
10-03 23:00:06
|
05-16 23:31:00
|
x
|
๋๋น๋
|
Pandas์ ํ์ฉ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
|
10-03 22:30:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
Pandas์ ์ฐ์ฐ๊ณผ ํจ์ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
|
10-03 22:00:02
|
05-16 23:31:00
|
x
|
๋๋น๋
|
Pandas์ ๊ธฐ๋ณธ ์ฌ์ฉ๋ฒ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
|
10-03 21:45:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ค๊ธ Captcha Hacking โค - ํดํน ์๋ํ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ] (CTF Captcha Hacking Project โค)
|
10-02 22:30:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ค๊ธ Captcha Hacking โฃ - KNN ๋ชจ๋ธ ํ์ต [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ] (CTF Captcha Hacking Project โฃ)
|
10-02 22:00:01
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ค๊ธ Captcha Hacking โข - ๋ฐ์ดํฐ ์ ์ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ] (CTF Captcha Hacking Project โข)
|
10-02 21:30:04
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ค๊ธ Captcha Hacking โก - ๋ฐ์ดํฐ ์์ง๊ณผ ๋ถ์ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ] (CTF Captcha Hacking Project โก)
|
10-02 20:30:00
|
05-16 23:31:00
|
x
|
๋๋น๋
|
์ค๊ธ Captcha Hacking โ - Problem Define [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ] (CTF Captcha Hacking Project โ )
|
10-02 20:00:10
|
05-16 23:31:00
|
x
|
๋๋น๋
|
KNN ์ซ์ ์ธ์ ์์ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
|
09-25 22:30:04
|
05-16 23:31:00
|
x
|
๋๋น๋
|
KNN ์๊ณ ๋ฆฌ์ฆ [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ] (KNN Algorithm)
|
09-25 21:30:01
|
05-16 23:31:00
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๋๋น๋
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OpenCV Filtering [ Python ๋ฐ์ดํฐ ๋ถ์๊ณผ ์ด๋ฏธ์ง ์ฒ๋ฆฌ ]
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09-22 11:00:00
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05-16 23:31:00
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