Zobrazeno 1 - 10
of 132
pro vyhledávání: '"Joonho Kong"'
Publikováno v:
Journal of Cybersecurity and Privacy, Vol 4, Iss 2, Pp 223-240 (2024)
Situational awareness (SA) is of tremendous significance for successful operations in many domains, such as surveillance, humanitarian, search, and rescue missions, and national security. SA is particularly important for the defense sector, and is re
Externí odkaz:
https://doaj.org/article/d00ac1ad605a4da480e05d2648e0fbe2
Publikováno v:
AI, Vol 4, Iss 4, Pp 926-948 (2023)
Deep learning is employed in many applications, such as computer vision, natural language processing, robotics, and recommender systems. Large and complex neural networks lead to high accuracy; however, they adversely affect many aspects of deep lear
Externí odkaz:
https://doaj.org/article/3dcb79f22b474cb49f0c16efbf19005c
Publikováno v:
IEEE Access, Vol 11, Pp 68501-68511 (2023)
Edge data centers are increasingly deployed to improve response time of intelligent services. Due to the high computing demands for such services, edge data centers consume a considerable amount of power, generating excessive heat. To mitigate therma
Externí odkaz:
https://doaj.org/article/1cd5e6cef26a4d6783cc49aa9797594f
Publikováno v:
IEEE Access, Vol 11, Pp 42751-42763 (2023)
As recent machine translation models are mostly based on the attention-based neural machine translation (NMT), many well-known models such as Transformer or bidirectional encoder representations from Transformers (BERT) have been proposed. Along with
Externí odkaz:
https://doaj.org/article/75fca3e1ee2445d68bc56067149d3b6d
Row-Wise Product-Based Sparse Matrix Multiplication Hardware Accelerator With Optimal Load Balancing
Publikováno v:
IEEE Access, Vol 10, Pp 64547-64559 (2022)
Matrix multiplication is a main computation kernel of emerging workloads, such as deep neural networks and graph analytics. These workloads often exhibit high sparsity in data, which means a large portion of the elements in the data are zero-valued e
Externí odkaz:
https://doaj.org/article/aceb26fa4ab14f6bbc9804701b4f07d6
Publikováno v:
IET Computers & Digital Techniques, Vol 16, Iss 1, Pp 29-43 (2022)
Abstract Many recent research efforts have exploited data sparsity for the acceleration of convolutional neural network (CNN) inferences. However, the effects of data transfer between main memory and the CNN accelerator have been largely overlooked.
Externí odkaz:
https://doaj.org/article/ace7e778e7cf4e7296bc44054dbbaf99
Autor:
Ji Heon Lee, Young Seo Lee, Jeong Hwan Choi, Hussam Amrouch, Joonho Kong, Young-Ho Gong, Sung Woo Chung
Publikováno v:
IEEE Access, Vol 9, Pp 120715-120729 (2021)
Monolithic 3D (M3D) integration reduces the wire length, which eventually improves energy efficiency and performance compared to 2D integration. However, 3D integration inevitably causes higher on-chip temperature compared to 2D integration due to th
Externí odkaz:
https://doaj.org/article/20989edb02404bf5b3bc606e07969682
Autor:
Arslan Munir, Jisu Kwon, Jong Hun Lee, Joonho Kong, Erik Blasch, Alexander J. Aved, Khan Muhammad
Publikováno v:
IEEE Access, Vol 9, Pp 111938-111959 (2021)
Urban surveillance, of which airborne urban surveillance is a vital constituent, provides situational awareness (SA) and timely response to emergencies. The significance and scope of urban surveillance has increased manyfold in recent years due to th
Externí odkaz:
https://doaj.org/article/cba321746e70404aad2079cf59443609
Arithmetic Coding-Based 5-Bit Weight Encoding and Hardware Decoder for CNN Inference in Edge Devices
Publikováno v:
IEEE Access, Vol 9, Pp 166736-166749 (2021)
Convolutional neural networks (CNNs) have gained a huge attention for real-world artificial intelligence (AI) applications such as image classification and object detection. On the other hand, for better accuracy, the size of the CNNs’ parameters (
Externí odkaz:
https://doaj.org/article/31f3ea05a4a848299eb0ad715b9be4aa
Autor:
Joonho Kong, Jae Young Hur
Publikováno v:
IEEE Access, Vol 8, Pp 18558-18570 (2020)
Near-threshold computing (NTC) has recently emerged and been considered as a strong candidate for future energy-efficient computing. However, adverse impacts from process variation such as delay and power fluctuations within die as well as across die
Externí odkaz:
https://doaj.org/article/74bd58e3e6ac4098b6676dd5c5cd20f8