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¢º °¿¬Á¦¸ñ:
Introduction to Deep Learning with PyTorch
RNN and LSTM implementation
¿¬»ç: ±èÇöö ±³¼ö / °æºÏ´ë ÀΰøÁö´ÉÇаú
Title: Introduction to Deep Learning with PyTorch
RNN and LSTM implementation
Abstract :
º» °ÀÇ¿¡¼´Â µÎ°³ÀÇ ÁÖÁ¦·Î ÁøÇàµÇ´Âµ¥ ù ¹ø° ÁÖÁ¦´Â “Introduction to Deep Learning with PyTorch”·Î PyTorch ÇÁ·¹ÀÓ¿öÅ©¸¦ ÀÌ¿ëÇÏ¿© PyTorch ±âº» ÀÍÈ÷±â, ½Å°æ¸Á (Neural network)¸ðµ¨ ±¸¼ºÇÏ´Â ¹æ¹ýÀ» ½Ç½ÀÀ» ÅëÇØ ÀÌÇØÇÏ´Â °ÍÀ» ¸ñÇ¥·Î ÇÑ´Ù. ±×¸®°í µÎ ¹ø° ÁÖÁ¦·Î´Â “RNN and LSTM implementation”·Î ¼øȯ ½Å°æ¸Á (Recurrent neural network, RNN)°ú ¼øȯ ½Å°æ¸ÁÀÇ Àå±â ÀÇÁ¸¼º ¹®Á¦¸¦ º¸¿ÏÇÑ Àå´Ü ±â ¸Þ¸ð¸®(Long short-term memory, LSTM) ¸ðµ¨µéÀ» ´Ù·ïº¸°íÀÚ ÇÑ´Ù.
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2021. 9 ~ ÇöÀç , °æºÏ´ëÇб³ ÀΰøÁö´ÉÇаú Á¶±³¼ö
2019. 9 ~ 2021. 8, Postdoctoral Fellow at Harvard Medical School
2019. 3 ~ 2019. 8, °í·Á´ëÇб³ ³ú°øÇבּ¸¼Ò ¿¬±¸±³¼ö
2019. 2, °í·Á´ëÇб³ ³ú°øÇаú ¹Ú»ç
ȨÆäÀÌÁö
https://sites.google.com/view/knuneuroai/home?authuser=0
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¢º °¿¬Á¦¸ñ:
Convolutional Neural Network implementation
¿¬»ç: Á¤Èñö ±³¼ö / °æºÏ´ëÇб³ ÀΰøÁö´ÉÇаú
Title: Convolutional Neural Network implementation
Abstract :
º» °ÀǸ¦ ÅëÇØ À̹ÌÁö ÀνÄÀ» À§ÇÑ Convolutional Neural Network (CNN) ±â¹ÝÀÇ µö·¯´× ±â¹ý¿¡ ´ëÇØ ÇнÀÇÑ´Ù. ¸ÕÀú, CNNÀ» ±¸¼ºÇÏ°í ÀÖ´Â convolution ¿¬»ê ¹× pooling ¿¡ ´ëÇÑ ±âÃÊ À̷п¡ ´ëÇØ ÇнÀÇÏ°í, CNN ±â¹ÝÀÇ ÃֽŠ¾ÆÅ°ÅØÃÄ¿¡ ´ëÇØ ¼Ò°³ÇÑ´Ù. ¶ÇÇÑ, ±¸±Û colab ±â¹ÝÀÇ È¯°æ¿¡¼ AlexNet, ResNet ¿¡ ´ëÇÑ ¾ÆÅ°ÅØÃĸ¦ pytorch¸¦ ÀÌ¿ëÇÏ¿© ±¸ÇöÇÏ´Â ½Ç½ÀÀ» ÁøÇàÇÑ´Ù. ¸¶Áö¸·À¸·Î, À̹ÌÁö ÀνķüÀ» Çâ»ó½ÃÅ°±â À§ÇÑ ¾Ó»óºí ¹× µ¥ÀÌÅÍ Áõ° ±â¹ý µîÀÇ Å×Å©´Ð¿¡ ´ëÇØ ¼Ò°³ÇÑ´Ù.
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2019. 9 ~ ÇöÀç °æºÏ´ëÇб³ ÀΰøÁö´ÉÇаú Á¶±³¼ö
2019. 2 ~ 2019. 8 Çö´ëÀÚµ¿Â÷ AIR Lab Ã¥ÀÓ¿¬±¸¿ø
2018. 8 Çѱ¹°úÇбâ¼ú¿ø Àü±â¹×ÀüÀÚ°øÇкΠ¹Ú»ç
2018. 8 Çѱ¹°úÇбâ¼ú¿ø Àü±â¹×ÀüÀÚ°øÇкΠ¹Ú»ç
ȨÆäÀÌÁö
https://sites.google.com/view/kvl/home?authuser=0
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¢º °¿¬Á¦¸ñ:
Introduction to computer vision with PyTorch
¿¬»ç: ¹é½Â·Ä ±³¼ö / UNIST Dept. of CS & AI
Title: Introduction to computer vision with PyTorch
Abstract :
In this lecture, we will learn how to extend the deep learning method proposed in the context of the image classification task towards more complex computer vision applications. In particular, we will deal with computer vision applications such as object detection and image generation as the main topics. Firstly, we will review the basic deep learning theory and PyTorch. Then we will learn detailed implementation methods for neural networks operating on object detection and image generation applications.
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2020~ ¿ï»ê°úÇбâ¼ú¿ø (UNIST) ÀΰøÁö´É´ëÇпø Á¶±³¼ö
2019 Research Intern at INRIA Sophia Antipolis
2020 PhD at Dept. of EEE, Imperial College London
ȨÆäÀÌÁö
https://sites.google.com/site/bsrvision00/
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¢º °¿¬Á¦¸ñ:
;Bridging CV and NLP with PyTorch
¿¬»ç: ±èÁØ¿µ ±³¼ö / Áß¾Ó´ë AIÇаú
Title: Bridging CV and NLP with PyTorch
Abstract :
º» °ÀÇ¿¡¼´Â ÃÖ±Ù È°¹ßÈ÷ ¿¬±¸µÇ°í ÀÖ´Â ÀÖ´Â ÄÄÇ»ÅÍ ºñÀü°ú ÀÚ¿¬¾î 󸮸¦ ÀÕ´Â "Visual Language Reasoning" ºÐ¾ß¿¡ ´ëÇØ °øºÎÇÏ°í, ½Ç½ÀÀ» ÅëÇØ Äڵ带 ÀÌÇØÇÏ´Â °ÍÀ» ¸ñÇ¥·Î ÇÑ´Ù. º» °ÀÇ¿¡¼ ´Ù·ê ³»¿ëÀº À̹ÌÁö ÁúÀÇ ÀÀ´ä, ºñµð¿À ÁúÀÇ ÀÀ´ä, ºñµð¿À ´ëÈ, ±×¸®°í À̹ÌÁö¸¦ ÅëÇÑ °ú°Å, ÇöÀç, ¹Ì·¡ Ãß·ÐÀÇ 4 °¡Áö ÁÖÁ¦¿¡ ´ëÇØ ´Ù¾çÇÑ ¹æ¹ý·Ð°ú À̸¦ ±¸ÇöÇÏ´Â °ÍÀÌ´Ù. º» °Á¸¦ ÅëÇØ PyTorch¸¦ È°¿ëÇÏ¿© À̹ÌÁö, ºñµð¿À, ÀÚ¿¬¾î¸¦ ´Ù·ç±â À§ÇÑ ´Ù¾çÇÑ Transformer ¸ðµ¨À» ´Ù·çµµ·Ï ÇÑ´Ù.
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2022.03 ~ ÇöÀç : Áß¾Ó´ëÇб³ ÀΰøÁö´ÉÇаú Á¶±³¼ö
2021.03 ~ 2022.02 : Çѱ¹°úÇбâ¼ú¿ø ¹Ú»çÈÄ¿¬±¸¿ø
2020.12 ~ 2021.06 : MSRA ¿¬±¸ÀÎÅÏ
2017.03 ~ 2021.02 : Çѱ¹°úÇбâ¼ú¿ø Àü±â¹×ÀüÀÚ°øÇкΠ¹Ú»ç
ȨÆäÀÌÁö
https://sites.google.com/view/imr-lab/family?authuser=0
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