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Meng Lyu, Wei Wang, Hao Wang, Haichao Wang et al. • Scientific Reports
(2017)
In this manuscript, we propose a novel framework of computational ghost imaging, i.e., ghost imaging using deep learning (GIDL). With a set of images reconstructed using traditional GI and the corresponding ground-truth counterparts, a deep...
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DOI: https://doi.org/10.1038/s41598-017-18171-7
PMC: 5736587
ZHANG Bin1, YIN Haoyu2, ZHANG Tengfei2, WANG Jiangyu1, LU Di1, WANG Lianjie1 • Yuanzineng kexue jishu
(2026)
To meet the computational efficiency requirements for multi-physics simulations in the design and development of advanced reactor cores, a neural network-based acceleration method was investigated for multi-physics coupling calculations in ...
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Open Access (DOAJ)
DOI: 10.7538/yzk.2025.youxian.0668
Sheng Ren, Rui Cao, Wenxue Tan, Yayuan Tang • IEEE Access
(2024)
The single image super-resolution based on deep learning has achieved extraordinary performance. However, due to inevitable environmental or technological limitations, some images not only have low resolution but also low brightness. The ex...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3403096
Jing Liu, Xuesong Hai, Keqin Li • Future Internet
(2023)
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their ...
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Open Access (DOAJ)
DOI: 10.3390/fi16010006
Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Sepp Hochreiter • Frontiers in Environmental Science
(2016)
The Tox21 Data Challenge has been the largest effort of the scientific community to compare computational methods for toxicity prediction. This challenge comprised 12,000 environmental chemicals and drugs which were measured for 12 differen...
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DOI: https://doi.org/10.3389/fenvs.2015.00080
Hui Fang, Danning Zhang, Yiheng Shu, Guibing Guo • ACM Transactions on Information Systems
(2020)
In the field of sequential recommendation, deep learning--(DL) based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov chain-based and factorization-based ones. However, there is ...
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Open Access
DOI: https://doi.org/10.1145/3426723
Sai Sri Hemantha Konala, Srinivas Koppu • Frontiers in Medicine
(2026)
IntroductionKidney-related disorders are one of the global health concerns that require timely detection to prevent severe health complications. The use of computed tomography (CT) images for accurate classification of kidney diseases is im...
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Open Access (DOAJ)
DOI: 10.3389/fmed.2026.1893419
Qiang Zhao, Rundong Guo, Xiaowei Feng, Weifeng Hu et al. • Mathematics
(2022)
Legal judgement prediction (LJP) is a crucial part of legal AI, and its goal is to predict the outcome of a case based on the information in the description of criminal facts. This paper proposes a decision prediction method based on causal...
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Open Access (DOAJ)
DOI: 10.3390/math10132281
Saleh Albahli • Future Internet
(2019)
Since the introduction of just-in-time effort aware defect prediction, many researchers are focusing on evaluating the different learning methods, which can predict the defect inducing changes in a software product. In order to predict thes...
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Open Access (DOAJ)
DOI: 10.3390/fi11120246
Qing Chen, Aihuang Guo, Yaodong Cui • Applied Sciences
(2024)
To achieve the anticipated performance of massive multiple input multiple output (MIMO) systems in wireless communication, it is imperative that the user equipment (UE) accurately feeds the channel state information (CSI) back to the base s...
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Open Access (DOAJ)
DOI: 10.3390/app14041356
Theodore Spaide, PhD, Anand E. Rajesh, MD, Nayoon Gim, Marian Blazes, MD et al. • Ophthalmology Science
(2025)
Purpose: To apply methods for quantifying uncertainty of deep learning segmentation of geographic atrophy (GA). Design: Retrospective analysis of OCT images and model comparison. Participants: One hundred twenty-six eyes from 87 participant...
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Open Access (DOAJ)
DOI: 10.1016/j.xops.2024.100587
Sidharth Mudgal, Han Li, Theodoros Rekatsinas, AnHai Doan et al. • ACM SIGMOD International Conference on Management of Data (SIGMOD)
(2018)
Entity matching (EM) finds data instances that refer to the same real-world entity. In this paper we examine applying deep learning (DL) to EM, to understand DL's benefits and limitations. We review many DL solutions that have been develope...
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DOI: https://doi.org/10.1145/3183713.3196926
Anton S. Becker, Magda Marcon, Soleen Ghafoor, Moritz C. Wurnig et al. • Investigative Radiology
(2017)
OBJECTIVES: The aim of this study was to evaluate the diagnostic accuracy of a multipurpose image analysis software based on deep learning with artificial neural networks for the detection of breast cancer in an independent, dual-center mam...
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DOI: https://doi.org/10.1097/rli.0000000000000358
Shutao Li A, Weiwei Song, Leyuan Fang, Yushi Chen et al. • IEEE Transactions on Geoscience and Remote Sensing
(2019)
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine ...
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Open Access
DOI: https://doi.org/10.1109/tgrs.2019.2907932
Ajeet Ram Pathak, Manjusha Pandey, Siddharth Swarup Rautaray • Procedia Computer Science
(2018)
The ubiquitous and wide applications like scene understanding, video surveillance, robotics, and self-driving systems triggered vast research in the domain of computer vision in the most recent decade. Being the core of all these applicatio...
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DOI: https://doi.org/10.1016/j.procs.2018.05.144
Lei Zhou, Chu Zhang, Fei Liu, Zhengjun Qiu et al. • Comprehensive Reviews in Food Science and Food Safety
(2019)
Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food sci...
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DOI: https://doi.org/10.1111/1541-4337.12492
Yu Lyu, Xiaolin Tian • Bioengineering
(2023)
Deep learning technology has achieved breakthrough research results in the fields of medical computer vision and image processing. Generative adversarial networks (GANs) have demonstrated a capacity for image generation and expression abili...
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Open Access (DOAJ)
DOI: 10.3390/bioengineering10091091
Ajantha Vijayakumar, Joseph Abraham Sundar Koilraj, Muthaiah Rajappa • International Journal of Computational Intelligence Systems
(2025)
Abstract Oral dosage forms are the most widely employed method of drug delivery in therapeutic treatments. However, the presence of visual defects in blister packages can adversely affect the drug's bioavailability and therapeutic efficacy,...
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Open Access (DOAJ)
DOI: 10.1007/s44196-025-00986-2
Shuo Han, Bo Mo, Junwei Xu, Shizun Sun et al. • International Journal of Computational Intelligence Systems
(2024)
Abstract Infrared images of sensitive targets are difficult to obtain and cannot meet the design and training needs of target detection and tracking algorithms for mobile platforms such as aircraft. This paper proposes an image translation ...
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Open Access (DOAJ)
DOI: 10.1007/s44196-024-00674-7
Jeffrey C. Kimmel, Andrew D. Mcdole, Mahmoud Abdelsalam, Maanak Gupta et al. • IEEE Access
(2021)
Several organizations are utilizing cloud technologies and resources to run a range of applications. These services help businesses save on hardware management, scalability and maintainability concerns of underlying infrastructure. Key clou...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3077498