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Showing 20 of 739 academic articles
saeedeh zebhi, Seyed Mohammad Taghi AlModaressi, Vahid Abootalebi • AUT Journal of Electrical Engineering
(2021)
In this paper, two different methods of human activity recognition based on video signals are introduced. The first method explores the effectiveness of combining feature descriptors obtained by local descriptors and artificial neural network ...
DOAJ
Open Access (DOAJ)
DOI: 10.22060/eej.2020.18517.5357
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 ...
OPENALEX
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 Liu, Xuesong Hai, Keqin Li • Future Internet
(2023)
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/fi16010006
Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Sepp Hochreiter • Frontiers in Environmental Science
(2016)
The Tox21 Data Challenge has been the largest effort of the scientific community to compare computational methods for toxicity prediction. This challenge comprised 12,000 environmental chemicals and drugs which were measured for 12 differen...
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DOI: https://doi.org/10.3389/fenvs.2015.00080
Longqian Huang, Ruichen Luo, Xü Liu, Xiang Hao • Light Science & Applications
(2022)
The goal of spectral imaging is to capture the spectral signature of a target. Traditional scanning method for spectral imaging suffers from large system volume and low image acquisition speed for large scenes. In contrast, computational sp...
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DOI: https://doi.org/10.1038/s41377-022-00743-6
PMC: 8927154
Bryan Y. Lim, Stefan Zohren • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
(2021)
Numerous deep learning architectures have been developed to accommodate the diversity of time-series datasets across different domains. In this article, we survey common encoder and decoder designs used in both one-step-ahead and multi-hori...
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Open Access
DOI: https://doi.org/10.1098/rsta.2020.0209
Saleh Albahli • Future Internet
(2019)
Since the introduction of just-in-time effort aware defect prediction, many researchers are focusing on evaluating the different learning methods, which can predict the defect inducing changes in a software product. In order to predict thes...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/fi11120246
Hao Shi, Guo Cao, Youqiang Zhang, Zixian Ge et al. • Remote Sensing
(2022)
Deep learning (DL) has recently been a core ingredient in modern computer vision tasks, triggering a wave of revolutions in various fields. The hyperspectral image (HSI) classification task is no exception. A wide range of DL-based methods ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14174235
Lei Zhou, Chu Zhang, Fei Liu, Zhengjun Qiu et al. • Comprehensive Reviews in Food Science and Food Safety
(2019)
Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food sci...
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DOI: https://doi.org/10.1111/1541-4337.12492
Andrea Steuwe, Birte Valentin, Oliver T. Bethge, Alexandra Ljimani et al. • Diagnostics
(2022)
Deep-learning (DL) noise reduction techniques in computed tomography (CT) are expected to reduce the image noise while maintaining the clinically relevant information in reduced dose acquisitions. This study aimed to assess the size, attenu...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/diagnostics12071627
Ajay Shrestha, Ausif Mahmood • IEEE Access
(2019)
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars, predictive forecasting, and speech recognition. The pain...
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Open Access
DOI: https://doi.org/10.1109/access.2019.2912200
Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht • Journal Of Big Data
(2021)
Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augme...
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DOI: https://doi.org/10.1186/s40537-021-00492-0
PMC: 8287113
Cyprien Alexandre, Rodolphe Devillers, David Mouillot, Raphael Seguin et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2024)
Detecting and tracking ships remotely is now required in a wide range of contexts, from military security to illegal immigration control, as well as the management of fisheries and marine protected areas. Among the available methods, radar ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2024.3437187
Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza et al. • BMC Medical Informatics and Decision Making
(2025)
Abstract Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), providing accurate disease classification and diagnosis. However, challenges such as inter- and intra-class similarities, class imba...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12911-025-02966-0
Md Mijanur Rahman, Ashik Uzzaman, Sadia Islam Sami, Fatema Khatun et al. • IET Image Processing
(2024)
Abstract This study introduces a novel encoder–decoder framework based on deep neural networks and provides a thorough investigation into the field of automatic picture captioning systems. The suggested model uses a “long short‐term memory”...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/ipr2.13287
Chao Zuo, Jiaming Qian, Shijie Feng, Wei Yin et al. • Light Science & Applications
(2022)
With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, n...
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DOI: https://doi.org/10.1038/s41377-022-00714-x
PMC: 8866517
Khawja Imran Masud, Md Yasin Zihad, Mehedi Hasan Shuvo, Mst Raonik Jannat et al. • PLoS ONE
(2026)
Early and real-time detection of rice leaf diseases (RLD) poses a significant challenge for farmers, especially in rural regions with limited access to advanced technology. Conventional deep learning models often require substantial computa...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0356383
Yihan Chen, Xingyu Gu, Zhen Liu, Jia Liang • Remote Sensing
(2022)
Traditional automatic pavement distress detection methods using convolutional neural networks (CNNs) require a great deal of time and resources for computing and are poor in terms of interpretability. Therefore, inspired by the successful a...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14081877
Xuedan Du, Yinghao Cai, Shuo Wang, Leijie Zhang • Youth Academic Annual Conference of Chinese Association of Automation (YAC)
(2016)
In recent years, deep learning has achieved great success in many fields, such as computer vision and natural language processing. Compared to traditional machine learning methods, deep learning has a strong learning ability and can make be...
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DOI: https://doi.org/10.1109/yac.2016.7804882