Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Chris H. Q. Ding"'
A novel classification algorithm for customer churn prediction based on hybrid Ensemble-Fusion model
Autor:
Chenggang He, Chris H. Q. Ding
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-25 (2024)
Abstract Nowadays, customer churn issues are becoming more and more important, which is one of the most important metrics for evaluating the health of a business it is difficult to measure success without measuring customer churn metrics. However, it
Externí odkaz:
https://doaj.org/article/93786b4b19a24e8889a9b61504783e19
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 10 (2022)
Most visual saliency computing methods build models based on the content of an image without considering the colorized effects. Biologically, human attention can be significantly influenced by color. This study firstly investigates the sole contribut
Externí odkaz:
https://doaj.org/article/57a5550341484f2b8525000b51086e5b
Autor:
Chenggang He, Chris H. Q. Ding
Publikováno v:
Applied Sciences, Vol 12, Iss 1, p 91 (2021)
Partner’s digital transformation is one of the most important metrics for businesses, particularly for businesses in the subscription world. Hence, how to predict partner transformation is a consistent focus in the industry. In this paper, we use a
Externí odkaz:
https://doaj.org/article/5e719444ac674182b06cb2eb5bdfbc29
Publikováno v:
Remote Sensing, Vol 12, Iss 21, p 3603 (2020)
Image segmentation has made great progress in recent years, but the annotation required for image segmentation is usually expensive, especially for remote sensing images. To solve this problem, we explore semi-supervised learning methods and appropri
Externí odkaz:
https://doaj.org/article/88020c56031d4eee837d49677c6565aa
Publikováno v:
IEEE Transactions on Medical Imaging. 42:1388-1400
Well-annotated medical datasets enable deep neural networks (DNNs) to gain strong power in extracting lesion-related features. Building such large and well-designed medical datasets is costly due to the need for high-level expertise. Model pre-traini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54649de9ce69398a9272cb1be20f3b6a
https://doi.org/10.1109/tmi.2022.3228254
https://doi.org/10.1109/tmi.2022.3228254
Publikováno v:
Neurocomputing. 481:1-10
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dcbb8637523b3b3ab1185bc9f4fe25eb
https://doi.org/10.1016/j.neucom.2022.01.053
https://doi.org/10.1016/j.neucom.2022.01.053
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. :1-10
Although neural networks have achieved great success in various fields, applications on mobile devices are limited by the computational and storage costs required for large models. The model compression (neural network pruning) technology can signifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::449e59d6a180b97d116e2b5d9ce0ae20
https://doi.org/10.1109/tnnls.2022.3165123
https://doi.org/10.1109/tnnls.2022.3165123
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::687f60ea1fa1d350d7f9ead4c1db8b39
https://doi.org/10.1109/lgrs.2022.3157032
https://doi.org/10.1109/lgrs.2022.3157032
Publikováno v:
Journal of Physics: Conference Series. 1746:012073
In the research of bullet engraving comparison method at home and abroad, the traditional method is through visual observation by microscope, comparing line-type engraving of two bullets to distinct whether the line match, which is inefficient and ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2bd2e78d17f5e3a92e0a403ea5a27e68
https://doi.org/10.1088/1742-6596/1746/1/012073
https://doi.org/10.1088/1742-6596/1746/1/012073
Autor:
Chris H. Q. Ding
Publikováno v:
High-Performance Computing and Networking ISBN: 9783540644439
HPCN Europe
HPCN Europe
HPF coding examples of practical scientific algorithms are examined in detail, with the idea that on these simple but non-trivial examples, we can fairly well understand issues related to different data distributions, different parallel constructs, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27ecef7f101d976ffdf3ea33c203e218
https://doi.org/10.1007/bfb0037149
https://doi.org/10.1007/bfb0037149
