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Academic Articles & Research Papers
Showing 20 of 150 academic articles
Naoya Matsumoto, Abhigyan Satyam, Mayya Geha, Mayya Geha et al. • Frontiers in Immunology
(2017)
C3a is important in the regulation of the immune response as well as in the development of organ inflammation and injury. Furthermore, C3a contributes to liver regeneration but its role in intestinal stem cell function has not been studied....
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Open Access (DOAJ)
DOI: 10.3389/fimmu.2017.01046
Matan Avitan, Elena V. Ravve, Zeev Volkovich • Mathematics
(2024)
Many different aspects of software system development and verification rely on precise function identification in binary code. Recognition of the source Assembly functions in embedded systems is one of the fundamental challenges in binary p...
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Open Access (DOAJ)
DOI: 10.3390/math12050658
John T. Harvey • The Cyber Defense Review
(2022)
Securing a nation’s cyber borders requires a high degree of coordination and openness among the relevant units, including real-time information sharing and threat assessment. Unfortunately, however, not only is there little incentive for pr...
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Open Access (DOAJ)
DOI: 10.55682/cdr/618t-rzgp
Miao Jiang, Honghui Chen • Applied Sciences
(2025)
Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine tran...
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Open Access (DOAJ)
DOI: 10.3390/app15052521
Harry R. Tennant • Defense Technical Information Center (DTIC)
(1981)
Despite a large amount of research on developing natural language understanding programs, little work has been done on evaluating their performance or potential. The evaluations that have been done have been unsystematic and incomplete. Thi...
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Xiao Chen Yang • Journal of Physics Conference Series
(2020)
Abstract Deep convolutional neural network (CNN) plays an important role in the field of computer vision and image processing. In order to further improve the performance of CNN, scholars have conducted a series of new explorations, such as...
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DOI: https://doi.org/10.1088/1742-6596/1693/1/012173
Wei Xue, Xiaoyan Xia, Pengcheng Wan, Ping Zhong et al. • Tsinghua Science and Technology
(2025)
Deep neural networks are commonly used in computer vision tasks, but they are vulnerable to adversarial samples, resulting in poor recognition accuracy. Although traditional algorithms that craft adversarial samples have been effective in a...
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Open Access (DOAJ)
DOI: 10.26599/TST.2024.9010029
Francisco Troncoso-Pastoriza, Javier López-Gómez, Lara Febrero-Garrido • Sensors
(2018)
This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporati...
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Open Access (DOAJ)
DOI: 10.3390/s18072364
Edward Pervin, Jon A. Webb • Defense Technical Information Center (DTIC)
(1982)
Computer vision and robotics suffer from not having good tools for manipulating three-dimensional objects. Vectors, coordinate geometry, and trigonometry all have deficiencies. Quaternions can be used to solve many of these problems. Many p...
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DOI: https://doi.org/10.21236/ada125076
Peter Meer, Doron Mintz, Azriel Rosenfeld, Dong Yoon Kim • International Journal of Computer Vision
(1991)
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DOI: https://doi.org/10.1007/bf00127126
Jie Lu, Wenpeng Zhang, Yongxiang Liu, Wei Yang • Remote Sensing
(2022)
The fine state of targets can be represented by the extracted micro-Doppler (m-D) components from the radar echo. However, current methods do not consider the specialty of the m-D components, and their performance with non-sinusoidal compon...
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Open Access (DOAJ)
DOI: 10.3390/rs14194764
Taikang Yuan, Junxing Zhu, Wuxin Wang, Jingze Lu et al. • Remote Sensing
(2023)
Sea surface temperature (SST) prediction has attracted increasing attention, due to its crucial role in understanding the Earth’s climate and ocean system. Existing SST prediction methods are typically based on either physics-based numerica...
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Open Access (DOAJ)
DOI: 10.3390/rs15143498
Zhiqiang Zhang, Yi Chen Zhao, Xiangke Liao, Wenqiang Shi et al. • Briefings in Functional Genomics
(2018)
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...
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DOI: https://doi.org/10.1093/bfgp/ely030
Boris Galitsky • Entropy
(2023)
It is well known that deep learning (DNN) has strong limitations due to a lack of explainability and weak defense against possible adversarial attacks. These attacks would be a concern for autonomous teams producing a state of high entropy ...
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Open Access (DOAJ)
DOI: 10.3390/e25111496
Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth et al. • International Journal of Computer Vision
(2019)
Abstract Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural images. Deep learning techniques have emerged as a ...
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DOI: https://doi.org/10.1007/s11263-019-01247-4
Ruichen Rong, Yonglong Wei, Lin Li, Tao Wang et al. • EBioMedicine
(2023)
Summary: Background: Tissues such as the liver lobule, kidney nephron, and intestinal gland exhibit intricate patterns of zonated gene expression corresponding to distinct cell types and functions. To quantitatively understand zonation, it...
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Open Access (DOAJ)
DOI: 10.1016/j.ebiom.2023.104698
Yanming Guo, Yu Liu, Ard Oerlemans, Songyang Lao et al. • Neurocomputing
(2015)
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Open Access
DOI: https://doi.org/10.1016/j.neucom.2015.09.116
Haotian Wu, Yan Guo, Juliang Cao, Zhiming Xiong et al. • Aerospace
(2025)
In response to the issues of severe pitch oscillation and unstable roll attitude present in existing reinforcement learning-based aircraft cruise control methods during dynamic maneuvers, this paper proposes a precise control method for air...
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Open Access (DOAJ)
DOI: 10.3390/aerospace12080670
Binghui Wang, Neil Zhenqiang Gong • IEEE Symposium on Security and Privacy (S&P)
(2018)
Hyperparameters are critical in machine learning, as different hyperparameters often result in models with significantly different performance. Hyperparameters may be deemed confidential because of their commercial value and the confidentia...
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Open Access
DOI: https://doi.org/10.1109/sp.2018.00038
Monika Dandotiya, Nikhil Kumar Goyal, Ajay Khunteta, Babita Tiwari • Scientific Reports
(2026)
Abstract Phishing attack continues to rank among the deadliest online threats. They create phony websites in an attempt to obtain personal data. This study offers a framework for a browser extension that uses machine learning to examine URL...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-35655-7