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Showing 20 of 2,192 academic articles
Richard Szeliski • Choice Reviews Online
(2011)
Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old ...
OPENALEX
DOI: https://doi.org/10.5860/choice.48-5140
Marco Antonio Contreras-Cruz, Juan Pablo Ramirez-Paredes, Uriel Haile Hernandez-Belmonte, Victor Ayala-Ramirez • Sensors
(2019)
One of the essential abilities in animals is to detect novelties within their environment. From the computational point of view, novelty detection consists of finding data that are different in some aspect to the known data. In robotics, re...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s19132965
Minqi Li, Xiangjian He, Kin‐Man Lam, Kaibing Zhang et al. • IET Image Processing
(2021)
Abstract Face hallucination is a super‐resolution technique specially designed to reconstruct high‐resolution faces from low‐resolution faces. Most state‐of‐the‐art algorithms leverage position‐patch prior knowledge of human faces to better...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/ipr2.12269
Bukola Peter Adedeji • World Electric Vehicle Journal
(2021)
Demand for pure electric vehicles has been found to be increasing over the years. This has necessitated the development of a model that would serve as a predicting machine for manufacturing different types of pure electric vehicles. Direct ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/wevj12040257
Xiaosai Duan, Suihuai Yu, Jianjie Chu, Dengkai Chen et al. • Buildings
(2022)
The assessment of indoor thermal environments is crucial to achieving thermal comfort and energy efficiency. However, the inaccurate evaluation and strong nonlinear variations of thermal comfort parameters limit engineering designs. Therefo...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/buildings12111880
Albert Nigrin • The MIT Press eBooks
(1993)
In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural network...
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DOI: https://doi.org/10.7551/mitpress/4923.001.0001
David M. Skapura (1995)
Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...
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Rui Zhang, Ranran Zhou, Zuting Zhong, Haifeng Qi et al. • Sensors
(2024)
Binarized convolutional neural networks (bCNNs) are favored for the design of low-storage, low-power cardiac arrhythmia classifiers owing to their high weight compression rate. However, multi-class classification of ECG signals based on bCN...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s24227207
Chunxu Qin, Yiran Ma, Huijuan Liang, Zhifan Wang et al. • Modelling
(2026)
The end-winding insulation structure of stator windings in pumped-storage generator units is complex, with pronounced electric field concentration under out-of-phase conditions, making them critical concerns in insulation design and conditi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/modelling7050190
Kevin M. Swingler (1996)
Techniques for building neural networks: introduction what are neural networks? how does neural computing differ from traditional programming? how are neural networks built? how do neural networks learn? what do I need to build an MLP? the ...
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Qi‐Jun Zhang, K.C. Gupta • Artech House, Inc. eBooks
(2000)
From the Publisher:
Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks information processing systems that can learn, generalize, and even allow model developm...
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John Hancock, Taghi M. Khoshgoftaar • Journal Of Big Data
(2020)
Abstract This survey investigates current techniques for representing qualitative data for use as input to neural networks. Techniques for using qualitative data in neural networks are well known. However, researchers continue to discover n...
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cc-by
DOI: https://doi.org/10.1186/s40537-020-00305-w
Jian Liu, Pei Niu, Yihui Jiang, Zilong Zhao et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2026)
Object detection in uncrewed aerial vehicle (UAV) acquired images remains a challenging task due to extreme scale variation, dense object layouts, and complex backgrounds, etc. Although convolutional neural networks (CNNs), transformers, an...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2026.3729713
Daniel Graupe • Advanced series in circuits and systems
(1997)
The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and compu...
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DOI: https://doi.org/10.1142/2982
• Choice Reviews Online
(2003)
A new, dramatically updated edition of the classic resource on the constantly evolving fields of brain theory and neural networks. Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook ...
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DOI: https://doi.org/10.5860/choice.41-0300
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
Xianfa Shi, Miao Su, Keun-sik Park • Journal of Theoretical and Applied Electronic Commerce Research
(2026)
Cross-border e-commerce offers consumers broader product access, yet uncertainty surrounding returns continues to suppress online purchase decisions. This study conceptualizes digital local return services as a digital assurance mechanism i...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/jtaer21060165
• Choice Reviews Online
(1996)
From the Publisher:
Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields ...
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DOI: https://doi.org/10.5860/choice.33-4484
Timothy D. Masters (1993)
This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to prod...
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Kevin Robert Gurney • CRC Press eBooks
(2018)
Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counte...
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DOI: https://doi.org/10.1201/9781315273570