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Academic Articles & Research Papers
Showing 20 of 26 academic articles
Sunada Satoshi, Yamaguchi Tomoya • EPJ Web of Conferences
(2023)
Photonic computing has attracted much attention due to its great potential to accelerate artificial neural network operations. However, the processing of a large amount of data, such as image data, basically requires large-scale photonic ci...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/epjconf/202328713007
Feng‐Chang Gu • IET Science, Measurement & Technology
(2023)
Abstract Partial discharge (PD) detection is used to evaluate the insulation status of high‐voltage equipment. The most challenging aspect of traditional PD recognition is extracting features from the discharge signal. Accordingly, this stu...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/smt2.12137
Runze Li, Yibo Dong, Fengsong Qian, Yiyang Xie et al. • PhotoniX
(2023)
Abstract The rapid development of neuromorphic computing has stimulated extensive research interest in artificial synapses. Optoelectronic artificial synapses using laser beams as stimulus signals have the advantages of broadband, fast resp...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s43074-023-00082-8
Aarush Saxena • International Journal for Research in Applied Science and Engineering Technology
(2022)
Abstract: The field of machine learning has taken a dramatic twist in re- cent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models can far exceed the per- performance of previous for...
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Open Access
DOI: https://doi.org/10.22214/ijraset.2022.47789
Zhiwen Xiong • EURASIP Journal on Wireless Communications and Networking
(2021)
Abstract Machine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and indus...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13638-021-02038-7
Yoav Goldberg • Journal of Artificial Intelligence Research
(2016)
Over the past few years, neural networks have re-emerged as powerful machine-learning models, yielding state-of-the-art results in fields such as image recognition and speech processing. More recently, neural network models started to be ap...
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DOI: https://doi.org/10.1613/jair.4992
Mandana Hamidi‐Haines, Zhongang Qi, Alan Fern, Fuxin Li et al. • Applied AI Letters
(2021)
Abstract We study a user‐guided approach for producing global explanations of deep networks for image recognition. The global explanations are produced with respect to a test data set and give the overall frequency of different “recognition...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/ail2.42
Bo Zhang • IEEE International Conference on Cognitive Informatics
(2010)
In object recognition (classification), it was known that the human brain processes visual information in semantic space mainly, that is, extracting the semantically meaningful features such as line-segments, boundaries, shape and so on. Bu...
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DOI: https://doi.org/10.1109/coginf.2010.5599750
Joseph Joel Pollak, Arnon Houri-Yafin, Seth J. Salpeter • Frontiers in Public Health
(2017)
Accurate malaria diagnosis is critical to prevent malaria fatalities, curb overuse of antimalarial drugs, and promote appropriate management of other causes of fever. While several diagnostic tests exist, the need for a rapid and highly acc...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpubh.2017.00219
Nikita Andriyanov • Mathematics
(2022)
On the one hand, the solution of computer vision tasks is associated with the development of various kinds of images or random fields mathematical models, i.e., algorithms, that are called traditional image processing. On the other hand, no...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/math10214021
Richard Boadu Antwi, Michael Kimollo, Samuel Yaw Takyi, Eren Erman Ozguven et al. • Smart Cities
(2024)
Advancements in computer vision are rapidly revolutionizing the way traffic agencies gather roadway geometry data, leading to significant savings in both time and money. Utilizing aerial and satellite imagery for data collection proves to b...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/smartcities7030059
Jinzhou Luo, Jiazhao Sun, Xiaoli Hao, Heng Liu et al. • Insects
(2026)
Myzus persicae is the most devastating piercing-sucking pest threatening tobacco production. Precise quantification of infestation severity is a prerequisite for precision pest management, making the integration of visual image analysis hig...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/insects17030305
Qingyang Xiao, Kaiyuan Liu, Yuhui Hong, Haixu Tang • ACS in focus
(2024)
In recent years, breakthroughs in artificial intelligence (AI) have dramatically transformed many fields. Developments in neural networks primarily drive the advances. These powerful models have demonstrated unprecedented capabilities in le...
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DOI: https://doi.org/10.1021/acsinfocus.7e8012
Uihoon Jung, Miseong Kim, Jaewon Jang, Jin‐Hyuk Bae et al. • Advanced Science
(2024)
Abstract With increasing demand for wearable electronics capable of computing huge data, flexible neuromorphic systems mimicking brain functions have been receiving much attention. Despite considerable efforts in developing practical neural...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/advs.202307494
Keiron O’Shea, Ryan Nash • arXiv (Cornell University)
(2015)
The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of art...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1511.08458
Myeongsuk Pak, Sang-Hoon Kim • International Conference on Computer Applications and Information Processing Technology (CAIPT)
(2017)
Deep learning has been the core topic in machine learning and convolutional neural network is one of the most prominent approaches. Convolutional neural network has won numerous competitions in recent years. It has outstanding results in im...
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DOI: https://doi.org/10.1109/caipt.2017.8320684
Yanhui Xi, Weijie Zhang, Feng Zhou, Xin Tang et al. • Energy Reports
(2023)
Accurate fault detection and classification help to analyze fault causes and quickly restore faulty phases. Deep learning can automatically extract fault features and identify fault types from the original three-phase voltage and current si...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.egyr.2022.12.043
Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, Zhen Wang et al. • European Heart Journal
(2019)
Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via...
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Open Access
DOI: https://doi.org/10.1093/eurheartj/ehz056
PMC: 6600129
Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, Alexander J. McKeeken et al. • Methods in Ecology and Evolution
(2022)
Abstract Deep learning is driving recent advances behind many everyday technologies, including speech and image recognition, natural language processing and autonomous driving. It is also gaining popularity in biology, where it has been use...
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DOI: https://doi.org/10.1111/2041-210x.13901
Gary Marcus • arXiv (Cornell University)
(2018)
Although deep learning has historical roots going back decades, neither the term "deep learning" nor the approach was popular just over five years ago, when the field was reignited by papers such as Krizhevsky, Sutskever and Hinton's now cl...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1801.00631