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Academic Articles & Research Papers
Showing 20 of 445 academic articles
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
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
Daichi Kando, Satoshi Tomioka, Naoki Miyamoto, Ryosuke Ueda • Applied Sciences
(2019)
In an optical measurement system using an interferometer, a phase extracting technique from interferogram is the key issue. When the object is varying in time, the Fourier-transform method is commonly used since this method can extract a ph...
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Open Access (DOAJ)
DOI: 10.3390/app9173529
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
Jiaxi Tang, Yaqin Zhao, Liqi Feng, Wenxuan Zhao • Animals
(2022)
Camera traps are widely used in wildlife research, conservation, and management, and abundant images are acquired every day. Efficient real-time instance segmentation networks can help ecologists label and study wild animals. However, exist...
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Open Access (DOAJ)
DOI: 10.3390/ani12151980
Luke de Oliveira • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
(2022)
Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...
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DOI: https://doi.org/10.1007/jhep07%282016%29069
Luke de Oliveira, Michael Kagan, Lester W. Mackey, Benjamin Philip Nachman et al. • Journal of High Energy Physics
(2016)
Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...
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DOI: https://doi.org/10.1007/jhep07(2016)069
Intisar Rizwan I Haque, Jeremiah J. Neubert • Informatics in Medicine Unlocked
(2020)
The review covers automatic segmentation of images by means of deep learning approaches in the area of medical imaging. Current developments in machine learning, particularly related to deep learning, are proving instrumental in identificat...
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DOI: https://doi.org/10.1016/j.imu.2020.100297
Lijian Zhang, Guangfu Liu • Advances in Mathematical Physics
(2021)
Ceramic image shape 3D image modeling focuses on of ceramic that was obtained from the camera imaging equipment such as 2D images, by normalization, gray, filtering denoising, wavelet image sharpening edge enhancement, binarization, and sha...
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Open Access (DOAJ)
DOI: 10.1155/2021/4343255
Wang, Dayong, Aditya Khosla, Rishab Gargeya, Humayun Irshad et al. • arXiv (Cornell University)
(2016)
The International Symposium on Biomedical Imaging (ISBI) held a grand challenge to evaluate computational systems for the automated detection of metastatic breast cancer in whole slide images of sentinel lymph node biopsies. Our team won bo...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1606.05718
Reza Shokri, Vitaly Shmatikov • ACM SIGSAC Conference on Computer and Communications Security (CCS)
(2015)
Deep learning based on artificial neural networks is a very popular approach to modeling, classifying, and recognizing complex data such as images, speech, and text. The unprecedented accuracy of deep learning methods has turned them into t...
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DOI: https://doi.org/10.1145/2810103.2813687
Ziwei Zhang, Peng Cui, Wenwu Zhu • IEEE Transactions on Knowledge and Data Engineering
(2020)
Deep learning has been shown to be successful in a number of domains, ranging from acoustics, images, to natural language processing. However, applying deep learning to the ubiquitous graph data is non-trivial because of the unique characte...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.2981333
S. Suganyadevi, V. Seethalakshmi, K. Balasamy • International Journal of Multimedia Information Retrieval
(2021)
Ongoing improvements in AI, particularly concerning deep learning techniques, are assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the quickest developing field in artificial intelligence and is ef...
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DOI: https://doi.org/10.1007/s13735-021-00218-1
PMC: 8417661
Szu-Pyng Kao, Yung-Chen Chang, Feng-Liang Wang • Sensors
(2023)
Bridges are often at risk due to the effects of natural disasters, such as earthquakes and typhoons. Bridge inspection assessments normally focus on cracks. However, numerous concrete structures with cracked surfaces are highly elevated or ...
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Open Access (DOAJ)
DOI: 10.3390/s23052572
Chang Min Hyun, Hwa Pyung Kim, Sung Min Lee, Sungchul Lee et al. • Physics in Medicine and Biology
(2018)
This paper presents a deep learning method for faster magnetic resonance imaging (MRI) by reducing k-space data with sub-Nyquist sampling strategies and provides a rationale for why the proposed approach works well. Uniform subsampling is u...
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DOI: https://doi.org/10.1088/1361-6560/aac71a
Sheng Zhang, Zhenghao Bei, Tonghua Ling, Qianqian Chen et al. • Scientific Reports
(2024)
Abstract Accurate detection of asphalt pavement distress is crucial for road maintenance and traffic safety. However, traditional convolutional neural networks usually struggle with this task due to the varied distress patterns and complex ...
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Open Access (DOAJ)
DOI: 10.1038/s41598-024-77173-4
Jason Riordon, Dušan Sovilj, Scott Sanner, David A. Sinton et al. • Trends in biotechnology
(2018)
Advances in high-throughput and multiplexed microfluidics have rewarded biotechnology researchers with vast amounts of data but not necessarily the ability to analyze complex data effectively. Over the past few years, deep artificial neural...
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DOI: https://doi.org/10.1016/j.tibtech.2018.08.005
Zhihao Wang, Jian Chen, Steven C. H. Hoi • IEEE Transactions on Pattern Analysis and Machine Intelligence
(2020)
Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning ...
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Open Access
DOI: https://doi.org/10.1109/tpami.2020.2982166
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