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Showing 20 of 3,028 academic articles
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...
DOAJ
Open Access (DOAJ)
DOI: 10.19678/j.issn.1000-3428.0069761
N. Kannaiya Raja, E. Laxmi Lydia, Thumpala Archana Acharya, K. Radhika et al. • IEEE Access
(2023)
In recent years, drones or Unmanned Aerial Vehicles (UAVs) got significant attention among researchers because of their extensive application in commercial applications, border surveillance, etc. As the conventional terrestrial communicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3324068
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...
OPENALEX
cc-by-nc
DOI: https://doi.org/10.1111/2041-210x.13901
Rui Zhao, Ruqiang Yan, Zhenghua Chen, Kezhi Mao et al. • Mechanical Systems and Signal Processing
(2018)
OPENALEX
Open Access
DOI: https://doi.org/10.1016/j.ymssp.2018.05.050
Yohei Nishizaki, Matias Valdivia, Ryoichi Horisaki, Katsuhisa Kitaguchi et al. • Optics Express
(2019)
We present a new class of wavefront sensors by extending their design space based on machine learning. This approach simplifies both the optical hardware and image processing in wavefront sensing. We experimentally demonstrated a variety of...
OPENALEX
Open Access
DOI: https://doi.org/10.1364/oe.27.000240
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...
OPENALEX
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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other-oa
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 ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s23052572
Sihan Zhou, Gene Thompson • Studies in Second Language Learning and Teaching
(2023)
Listening to academic content in English medium instruction (EMI) classrooms at university can be a demanding task for students who transition from first language (L1) instructed secondary schools. This longitudinal mixed methods study anal...
DOAJ
Open Access (DOAJ)
DOI: 10.14746/ssllt.38281
Georgios Petmezas, Grigorios-Aris Cheimariotis, Leandros Stefanopoulos, Bruno Rocha et al. • Sensors
(2022)
Respiratory diseases constitute one of the leading causes of death worldwide and directly affect the patient’s quality of life. Early diagnosis and patient monitoring, which conventionally include lung auscultation, are essential for the ef...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s22031232
Jianqing Fan, Cong Ma, Yiqiao Zhong • Statistical Science
(2021)
Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a l...
OPENALEX
Open Access
DOI: https://doi.org/10.1214/20-sts783
PMC: 8300482
Sebastian Macaluso, David Shih • Journal of High Energy Physics
(2018)
Abstract We apply computer vision with deep learning — in the form of a convolutional neural network (CNN) — to build a highly effective boosted top tagger. Previous work (the “DeepTop” tagger of Kasieczka et al) has shown that a CNN-based ...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/JHEP10(2018)121
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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cc-by
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
Christopher D. Manning • Computational Linguistics
(2015)
Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...
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Open Access
DOI: https://doi.org/10.1162/coli_a_00239
Jing Li, Aixin Sun, Jianglei Han, Chenliang Li • IEEE Transactions on Knowledge and Data Engineering
(2020)
Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc. NER always serves as the foundation for many natural language ...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tkde.2020.2981314
Ruihui Mu, Xiaoqin Zeng • KSII Transactions on Internet and Information Systems
(2019)
With the advent of big data, deep learning technology has become an important research direction in the field of machine learning, which has been widely applied in the image processing, natural language processing, speech recognition and on...
OPENALEX
Open Access
DOI: https://doi.org/10.3837/tiis.2019.04.001
Mehran Soltani, Vahid Pourahmadi, Ali Mirzaei, Hamid Sheikhzadeh • IEEE Communications Letters
(2019)
In this letter, we present a deep learning algorithm for channel estimation in communication systems. We consider the time-frequency response of a fast fading communication channel as a 2D image. The aim is to find the unknown values of the...
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Open Access
DOI: https://doi.org/10.1109/lcomm.2019.2898944
Gustau Camps‐Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein • Wiley eBooks
(2021)
Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only re...
OPENALEX
Open Access
DOI: https://doi.org/10.1002/9781119646181
Xue-Wen Chen, Xiaotong Lin • IEEE Access
(2014)
Deep learning is currently an extremely active research area in machine learning and pattern recognition society. It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/access.2014.2325029