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Academic Articles & Research Papers
Showing 20 of 25 academic articles
Aisha Muhammad Din, Sadia Jabeen • AAOU Journal
(2014)
One of the biggest challenges faced by online learning systems is the absence of opportunities for the practical exposure of the students, especially in professional degree programmes. The theoretical knowledge they gain is undoubtedly more...
DOAJ
Open Access (DOAJ)
DOI: 10.1108/AAOUJ-09-01-2014-B009
BOLDER Research Group • F1000Research
(2016)
Despite the many thousands of research studies published every year, evidence for making clinical decisions is often lacking. The main problem is that the evidence available is generated in conditions very different from those that prevail ...
DOAJ
Open Access (DOAJ)
DOI: 10.12688/f1000research.8392.1
Yu Zhang, Peter Tiňo B, Aleš Leonardis, Ke Tang • IEEE Transactions on Emerging Topics in Computational Intelligence
(2021)
Along with the great success of deep neural networks, there is also growing concern about their black-box nature. The interpretability issue affects people's trust on deep learning systems. It is also related to many ethical problems, e.g.,...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tetci.2021.3100641
C. H. Chen • McGraw-Hill, Inc. eBooks
(1996)
Fuzzy logic principles and algorithms design guidelines for fuzzy logic systems enhanced training algorithms maximum likelihood training temporal difference learning NADINE hybrid learning systems explanation and reasoning within connectivi...
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Anjana M S, Aryadevi Remanidevi Devidas, Maneesha Vinodini Ramesh • IEEE Access
(2025)
Electrical energy plays a pivotal role in modern society by powering homes, industries, and transportation systems. However, the production of electricity is associated with significant carbon emissions, primarily from fossil fuel-based pow...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3539333
Aziliz Le Glaz, Yannis Haralambous, Deok-Hee Kim-Dufor, Philippe Lenca et al. • Journal of Medical Internet Research
(2020)
BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides ...
OPENALEX
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DOI: https://doi.org/10.2196/15708
PMC: 8132982
Andrea Galassi, Marco Lippi, Paolo Torroni • IEEE Transactions on Neural Networks and Learning Systems
(2020)
Attention is an increasingly popular mechanism used in a wide range of neural architectures. The mechanism itself has been realized in a variety of formats. However, because of the fast-paced advances in this domain, a systematic overview o...
OPENALEX
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DOI: https://doi.org/10.1109/tnnls.2020.3019893
George K. Thiruvathukal, Yung-Hsiang Lu, Jaeyoun Kim, Yiran Chen et al. • Chapman & Hall/CRC eBooks
(2022)
Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Visio...
OPENALEX
Open Access
DOI: https://doi.org/10.1201/9781003162810
Mohaiminul Islam, Guorong Chen, Shangzhu Jin • American Journal of Neural Networks and Applications
(2019)
Neural networks represent a brain metaphor for information processing. These models are biologically inspired rather than an exact replica of how the brain actually functions. Neural networks have been shown to be very promising systems in ...
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DOI: https://doi.org/10.11648/j.ajnna.20190501.12
François Chollet, JJ Allaire (2018)
Introduces deep learning systems using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples...
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Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu et al. • IEEE Transactions on Neural Networks and Learning Systems
(2017)
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...
OPENALEX
DOI: https://doi.org/10.1109/tnnls.2017.2766168
Daniel W. Otter, Julian Richard Medina, Jugal Kumar Kalita • IEEE Transactions on Neural Networks and Learning Systems
(2020)
Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This article provides a brief introduction to the field and a quick overview of deep learni...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tnnls.2020.2979670
Mengnan Du, Fan Yang, Na Zou, Xia Hu • IEEE Intelligent Systems
(2020)
Fairness in deep learning has attracted tremendous attention recently, as deep learning is increasingly being used in high-stake decision making applications that affect individual lives. We provide a review covering recent progresses to ta...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/mis.2020.3000681
Mufti Mahmud, M. Shamim Kaiser, T. Martin McGinnity, Amir Hussain • Cognitive Computation
(2021)
Recent technological advancements in data acquisition tools allowed life scientists to acquire multimodal data from different biological application domains. Categorized in three broad types (i.e. images, signals, and sequences), these data...
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DOI: https://doi.org/10.1007/s12559-020-09773-x
PMC: 7783296
Xing Su, Shan Xue, Fanzhen Liu, Jia Wu et al. • IEEE Transactions on Neural Networks and Learning Systems
(2022)
Detecting a community in a network is a matter of discerning the distinct features and connections of a group of members that are different from those in other communities. The ability to do this is of great significance in network analysis...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tnnls.2021.3137396
Jaya Gupta, Sunil Kumar Pathak, Gireesh Kumar • Journal of Physics Conference Series
(2022)
Abstract Deep Learning is a machine learning area that has recently been used in a variety of industries. Unsupervised, semi-supervised, and supervised-learning are only a few of the strategies that have been developed to accommodate differ...
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DOI: https://doi.org/10.1088/1742-6596/2273/1/012029
Wei Wang, Meihui Zhang, Gang Chen, H. V. Jagadish et al. • ACM SIGMOD Record
(2016)
Deep learning has recently become very popular on account of its incredible success in many complex datadriven applications, including image classification and speech recognition. The database community has worked on data-driven application...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3003665.3003669
Mufti Mahmud, M. Shamim Kaiser, Amir Hussain, Stefano Vassanelli • IEEE Transactions on Neural Networks and Learning Systems
(2018)
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tnnls.2018.2790388
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...
OPENALEX
Open Access
DOI: https://doi.org/10.1162/coli_a_00239
Zhong‐Qiu Zhao, Peng Zheng, Shou-Tao Xu, Xindong Wu • IEEE Transactions on Neural Networks and Learning Systems
(2019)
Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tnnls.2018.2876865