Zobrazeno 1 - 10
of 217
pro vyhledávání: '"Jenq-Kuen Lee"'
Publikováno v:
IEEE Access, Vol 12, Pp 64193-64211 (2024)
In recent years, considerable research has focused on the use of custom hardware to accelerate deep learning on edge devices. However, the end-to-end flow of deep learning includes preprocessing and postprocessing. Deep learning hardware accelerators
Externí odkaz:
https://doaj.org/article/a9d4152c955543b58cb5ea8b0fb50374
Publikováno v:
IEEE Access, Vol 10, Pp 52630-52654 (2022)
Block-based tools can make it easier for beginners to learn programming by arranging blocks. Their block concept and extensible characteristics make block-based designs suitable for introductory programming. However, block-based tools are easy to use
Externí odkaz:
https://doaj.org/article/3e654ecbbdbc4020b4edbd1735388273
Publikováno v:
ACM Transactions on Design Automation of Electronic Systems. 28:1-21
Today, as deep learning (DL) is applied more often in daily life, dedicated processors such as CPUs and GPUs have become very important for accelerating model executions. With the growth of technology, people are becoming accustomed to using edge dev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3a024700d0e994a34de6dd844c1a924
https://doi.org/10.1145/3569939
https://doi.org/10.1145/3569939
Autor:
Geng-Ming Liang, Chuan-Yue Yuan, Meng-Shiun Yuan, Tai-Liang Chen, Kuan-Hsun Chen, Jenq-Kuen Lee
Publikováno v:
ICPP Workshops '22: Workshop Proceedings of the 51st International Conference on Parallel Processing, 1-8
STARTPAGE=1;ENDPAGE=8;TITLE=ICPP Workshops '22: Workshop Proceedings of the 51st International Conference on Parallel Processing
STARTPAGE=1;ENDPAGE=8;TITLE=ICPP Workshops '22: Workshop Proceedings of the 51st International Conference on Parallel Processing
Since the emergence of MLIR, High-level Synthesis (HLS) tools started to design in multi-level abstractions. Unlike the traditional HLS tools that are based on a single abstraction (e.g. LLVM), optimizations in different levels of abstraction could b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f558e2da06d20e2b5ed064d848a438d
https://research.utwente.nl/en/publications/c13bd558-10db-4f63-a8f4-d088ad4f5d3b
https://research.utwente.nl/en/publications/c13bd558-10db-4f63-a8f4-d088ad4f5d3b
Publikováno v:
Journal of Signal Processing Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ddf31320f5110be4f06baf65472e103
https://doi.org/10.1007/s11265-022-01821-z
https://doi.org/10.1007/s11265-022-01821-z
Autor:
Kuan-Hsun Chen, Chiahui Su, Christian Hakert, Sebastian Buschjäger, Chao-Lin Lee, Jenq-Kuen Lee, Katharina Morik, Jian-Jia Chen
Publikováno v:
ACM transactions on embedded computing systems. 21(6)
For timing-sensitive edge applications, the demand for efficient lightweight machine learning solutions has increased recently. Tree ensembles are among the state-of-the-art in many machine learning applications. While single decision trees are compa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64f4c98ca280d9cde62ff096c6cd183f
https://doi.org/10.1145/3508019
https://doi.org/10.1145/3508019
Publikováno v:
Workshop Proceedings of the 51st International Conference on Parallel Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2afeb2e8507ba3aabf60f4ffe7638e10
https://doi.org/10.1145/3547276.3548513
https://doi.org/10.1145/3547276.3548513
Publikováno v:
Workshop Proceedings of the 51st International Conference on Parallel Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ceb77b42d3dec86744dda939dc040a89
https://doi.org/10.1145/3547276.3548514
https://doi.org/10.1145/3547276.3548514
Autor:
Hung-Ming Lai, Jenq-Kuen Lee
Publikováno v:
Workshop Proceedings of the 51st International Conference on Parallel Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::318e2a6a7c935d0c038dabe49ac11e52
https://doi.org/10.1145/3547276.3548518
https://doi.org/10.1145/3547276.3548518
Publikováno v:
The Journal of Supercomputing. 77:10065-10096
With growing applications such as image recognition, speech recognition, ADAS, and AIoT, artificial intelligence (AI) frameworks are becoming popular in various industries. Currently, many choices for neural network frameworks exist for executing AI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8c9b434da562b5b68cb9778c7a8b005
https://doi.org/10.1007/s11227-021-03625-7
https://doi.org/10.1007/s11227-021-03625-7