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Academic Articles & Research Papers
Showing 20 of 2,192 academic articles
Risheng Wang, Tao Lei, Ruixia Cui, Bingtao Zhang et al. • IET Image Processing
(2022)
Abstract Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation us...
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DOI: https://doi.org/10.1049/ipr2.12419
He Li, Kaoru Ota, Mianxiong Dong • IEEE Network
(2018)
Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing ...
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Open Access
DOI: https://doi.org/10.1109/mnet.2018.1700202
Abderrazak Khediri, Ayoub Yahiaoui, Mohamed Ridda Laouar, Yacine Belhocine • Acta Informatica Pragensia
(2024)
Blackout events in smart grids can have significant impacts on individuals, communities and businesses, as they can disrupt the power supply and cause damage to the grid. In this paper, a new proactive approach to an early warning system fo...
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Open Access (DOAJ)
DOI: 10.18267/j.aip.246
Liyue Wu, Qinchuan Zhan, Yanjun Li • Humanities & Social Sciences Communications
(2026)
Abstract This study applies a multimodal deep learning approach to examine tourist engagement with traditional architectural heritage. The Gao Family Compound in Xi’an serves as a representative case. Social-media texts and images from Weib...
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Open Access (DOAJ)
DOI: 10.1057/s41599-026-07879-5
Yasha Ektefaie, William Yuan, Deborah A. Dillon, Nancy U. Lin et al. • npj Breast Cancer
(2021)
Abstract Histopathologic evaluation of biopsy slides is a critical step in diagnosing and subtyping breast cancers. However, the connections between histology and multi-omics status have never been systematically explored or interpreted. We...
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Open Access (DOAJ)
DOI: 10.1038/s41523-021-00357-y
Konstantinos Keremis, Eleni Vrochidou, George A. Papakostas • Journal of Imaging
(2025)
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empi...
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Open Access (DOAJ)
DOI: 10.3390/jimaging11090322
Zhen Li, Deqing Zou, Shouhuai Xu, Xinyu Ou et al. • Network and Distributed System Security Symposium
(2018)
The automatic detection of software vulnerabilities is an important research problem.However, existing solutions to this problem rely on human experts to define features and often miss many vulnerabilities (i.e., incurring high false negati...
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Open Access
DOI: https://doi.org/10.14722/ndss.2018.23158
Yair Rivenson, Zoltán S. Göröcs, Harun Günaydın, Yibo Zhang et al. • Optica
(2017)
We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired ...
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Open Access
DOI: https://doi.org/10.1364/optica.4.001437
Phillip M. Cheng, Emmanuel Montagnon, Rikiya Yamashita, Ian Pan et al. • Radiographics
(2021)
Deep learning is a class of machine learning methods that has been successful in computer vision. Unlike traditional machine learning methods that require hand-engineered feature extraction from input images, deep learning methods learn the...
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DOI: https://doi.org/10.1148/rg.2021200210
Fenglei Li, Qiaoyu Hu, Xianglei Zhang, Renhong Sun et al. • Nature Communications
(2022)
The rational design of PROTACs is difficult due to their obscure structure-activity relationship. Here the authors present a deep neural network model - DeepPROTACs - for predicting the degradation capacity of a proposed PROTAC molecule....
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Open Access (DOAJ)
DOI: 10.1038/s41467-022-34807-3
Chunlong Shao, Ning Zhang, Wei Du, Han Li et al. • Journal of Radiation Research and Applied Sciences
(2026)
Objective: This study was designed to examine the association between preoperative abdominal MRI features derived using a deep learning-based reconstruction (DL-Recon) algorithm and postoperative surgical incision-healing outcomes, while ev...
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Open Access (DOAJ)
DOI: 10.1016/j.jrras.2026.102395
Mingyu Zhao, Shujia Zhang, Ke Li, Yanru Zhang et al. • Frontiers in Robotics and AI
(2026)
Densely populated enclosed environments, characterized by complex thermal stratification and overlapping breathing zones, represent high-risk clusters for the airborne transmission of respiratory pathogens. To address the dual challenges of...
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Open Access (DOAJ)
DOI: 10.3389/frobt.2026.1846010
Yundie Guan, Xiangyu Zhang, Zheming Liang, Tao Chen • IET Renewable Power Generation
(2025)
Abstract The intermittency and volatility of renewable energy have been major challenges in modern power systems. This paper proposes a self‐adaptive energy management strategy based on deep reinforcement learning (DRL) to integrate renewab...
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Open Access (DOAJ)
DOI: 10.1049/rpg2.13192
Xinxin Yu, Yimeng Wang, Long Chen, Weihua Li et al. • Journal of Pharmaceutical Analysis
(2025)
Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid m...
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Open Access (DOAJ)
DOI: 10.1016/j.jpha.2025.101317
S. Chinnadurai, S. Selvakumar • Scientific Reports
(2025)
Abstract Cotton has, in recent years, become one of the most important cash crops worldwide while being impacted in yield from leaf disease which generally goes unnoticed in the early stage. Detection methods depend on manual efforts produc...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-28549-7
Wei Wang, Meihui Zhang, Gang Chen, H. V. Jagadish et al. • ACM SIGMOD Record
(2016)
Deep learning has recently become very popular on account of its incredible success in many complex datadriven applications, including image classification and speech recognition. The database community has worked on data-driven application...
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Open Access
DOI: https://doi.org/10.1145/3003665.3003669
Tyrone Bright, Sarp Adali, Cristina Trois • Drones
(2025)
As the generation of Municipal Solid Waste (MSW) has exponentially increased, this poses a challenge for waste managers, such as municipalities, to effectively control waste streams. If waste streams are not managed correctly, they negative...
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Open Access (DOAJ)
DOI: 10.3390/drones9080550
XIAO Zhipeng, HE Shufeng, TIAN Chunqi • Jisuanji gongcheng
(2025)
This study presents a facial emotion recognition network based on UniRepLKNet to address the difficulty in effectively capturing feature information and preventing key facial information from occupying a more prominent position in the facia...
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Open Access (DOAJ)
DOI: 10.19678/j.issn.1000-3428.0069761
Prot Piyakawanich, Pattarapong Phasukkit • Drones
(2024)
In the rapidly evolving domain of Unmanned Aerial Vehicles (UAVs), precise altitude estimation remains a significant challenge, particularly for lightweight UAVs. This research presents an innovative approach to enhance altitude estimation ...
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Open Access (DOAJ)
DOI: 10.3390/drones8120718
Swaraja K., Akshitha V., Pranav K., Vyshnavi B. et al. • E3S Web of Conferences
(2021)
Depth estimation is a computer vision technique that is critical for autonomous schemes for sensing their surroundings and predict their own condition. Traditional estimating approaches, such as structure from motion besides stereo vision s...
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Open Access (DOAJ)
DOI: 10.1051/e3sconf/202130901069