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1دورية أكاديمية
المؤلفون: Yosoeb Shin, Vikas Palakonda, Sangseok Yun, Il-Min Kim, Seon-Gon Kim, Sang-Mi Park, Jae-Mo Kang
المصدر: IEEE Access, Vol 12, Pp 8187-8197 (2024)
مصطلحات موضوعية: Classification, data augmentation, deep learning, image processing, supervised learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
وصف الملف: electronic resource
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2دورية أكاديمية
المؤلفون: Milad Khademi Nori, Yiqun Ge, Il-Min Kim
المصدر: IEEE Access, Vol 11, Pp 131623-131638 (2023)
مصطلحات موضوعية: Activation noise, autoencoder, data augmentation, regularization, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
وصف الملف: electronic resource
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3دورية أكاديمية
المؤلفون: Seong-Hwan Kang, Vikas Palakonda, Il-Min Kim, Jae-Mo Kang, Sangseok Yun
المصدر: Mathematics, Vol 11, Iss 18, p 3898 (2023)
مصطلحات موضوعية: computer vision, deep learning, non-maximum suppression, object detection, steel surface defect, Mathematics, QA1-939
وصف الملف: electronic resource
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4دورية أكاديمية
المؤلفون: Noel Han, Il-Min Kim, Jaewoo So
المصدر: Sensors, Vol 23, Iss 10, p 4929 (2023)
مصطلحات موضوعية: channel quality indicator feedback, long short-term memory, lightweight model, modulation and coding scheme, feedback overhead, Chemical technology, TP1-1185
وصف الملف: electronic resource
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5دورية أكاديمية
المؤلفون: Sunghoon Lee, Jooyoun Park, Il-Min Kim, Jun Heo
المصدر: EURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-12 (2021)
مصطلحات موضوعية: Polar codes, Soft-output decoding, Parallelization, Telecommunication, TK5101-6720, Electronics, TK7800-8360
وصف الملف: electronic resource
العلاقة: https://doaj.org/toc/1687-1499Test
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6دورية أكاديمية
المؤلفون: Jae-Mo Kang, Chang-Jae Chun, Il-Min Kim
المصدر: IEEE Access, Vol 8, Pp 121162-121181 (2020)
مصطلحات موضوعية: Autoencoder, channel estimation, convolutional neural network (CNN), deep learning, generative adversarial network (GAN), recurrent neural network (RNN), Electrical engineering. Electronics. Nuclear engineering, TK1-9971
وصف الملف: electronic resource
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7
المؤلفون: Sangseok Yun, Wan Choi, Il-Min Kim
المصدر: IEEE Internet of Things Journal. 9:16113-16127
مصطلحات موضوعية: Computer Networks and Communications, Hardware and Architecture, Signal Processing, Computer Science Applications, Information Systems
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::a78049fedcf2a84ed74ab4f131210889Test
https://doi.org/10.1109/jiot.2022.3152359Test -
8
المؤلفون: Jinyoung Lee, Sangseok Yun, Il-Min Kim, Jeongseok Ha
المصدر: IEEE Transactions on Vehicular Technology. 71:5615-5620
مصطلحات موضوعية: Computer Networks and Communications, Automotive Engineering, Aerospace Engineering, Electrical and Electronic Engineering
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::7fcff892e697e41401febe0af980175aTest
https://doi.org/10.1109/tvt.2022.3153926Test -
9
المؤلفون: Jae-Mo Kang, Sangseok Yun, Il-Min Kim, Heechul Jung
المصدر: IEEE Wireless Communications Letters. 11:622-626
مصطلحات موضوعية: Control and Systems Engineering, Electrical and Electronic Engineering
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::df585bdb3c763c51a2e6b2ac23b81d93Test
https://doi.org/10.1109/lwc.2021.3139024Test -
10
المؤلفون: Dong-Woo Ryu, Jae-Mo Kang, Sangseok Yun, Sangho Lee, Jeongseok Ha, Jihoe Kwon, Il-Min Kim
المصدر: IEEE Geoscience and Remote Sensing Letters. 19:1-5
مصطلحات موضوعية: Scheme (programming language), Data collection, Energy management, business.industry, Computer science, Deep learning, Computer Science::Neural and Evolutionary Computation, Geotechnical Engineering and Engineering Geology, Machine learning, computer.software_genre, Convolutional neural network, Vibration, Recurrent neural network, Reinforcement learning, Artificial intelligence, Electrical and Electronic Engineering, business, computer, computer.programming_language
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::f713f5cb84c8ceb0717b0de360313867Test
https://doi.org/10.1109/lgrs.2021.3067974Test