Results 11 to 20 of about 144,445 (263)
The unreasonable effectiveness of deep learning in artificial intelligence [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2020 Deep learning networks have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance. Although applications of deep learning networks to real-world problems have become ubiquitous, our understanding of why they are so effective is lacking.
Terrence J Sejnowski +1 more
exaly +4 more sources
Deep Learning on Medical Imaging in Identifying Kidney Stones: Review Paper [PDF]
E3S Web of Conferences, 2023 Medical imaging is currently using artificial intelligence-based technologies to aid evaluate diagnostic information images, particularly in enforcing kidney stones.
Sulaksono Nanang +2 more
doaj +1 more source
Deep Learning-Based Artificial Intelligence for Mammography [PDF]
Korean Journal of Radiology, 2021 During the past decade, researchers have investigated the use of computer-aided mammography interpretation. With the application of deep learning technology, artificial intelligence (AI)-based algorithms for mammography have shown promising results in the quantitative assessment of parenchymal density, detection and diagnosis of breast cancer, and ...
Jung Hyun Yoon, Eun-Kyung Kim
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The Role of Deep Learning Method Based on Environmental Geochemical Data in Resource [PDF]
E3S Web of Conferences, 2021 In recent years, with the continuous development of artificial intelligence, deep learning, as an important method of artificial intelligence learning, has made great progress.
Yao Pei
doaj +1 more source
Artificial Intelligence and Deep Learning for Rheumatologists
Arthritis & Rheumatology, 2022 Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing field of academic research and commercial applications across medicine. Deep learning could have particular relevance to rheumatology if correctly utilized.
Christopher McMaster +6 more
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UCL: Unsupervised Curriculum Learning for water body classification from remote sensing imagery
International Journal of Applied Earth Observations and Geoinformation, 2021 This paper presents a Convolutional Neural Networks (CNN) based Unsupervised Curriculum Learning approach for the recognition of water bodies to overcome the stated challenges for remote sensing based RGB imagery. The unsupervised nature of the presented
Nosheen Abid +6 more
doaj +1 more source
The Limitations of Deep Learning in Achieving Real Artificial Intelligence
Proceedings, 2022 The achievement of artificial intelligence has been one of the goals in the field of machine learning, and achievements in the field of deep learning have led to the idea that the goal of so-called “intelligence” in artificial intelligence can be ...
Tianqi Wu, Ruiqi Jin
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Discovering Themes in Deep Brain Stimulation Research Using Explainable Artificial Intelligence
Biomedicines, 2023 Deep brain stimulation is a treatment that controls symptoms by changing brain activity. The complexity of how to best treat brain dysfunction with deep brain stimulation has spawned research into artificial intelligence approaches. Machine learning is a
Ben Allen
doaj +1 more source
Artificial intelligence and deep learning in ophthalmology [PDF]
British Journal of Ophthalmology, 2018 Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image recognition, speech recognition and natural language processing, but is only beginning to impact on healthcare. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography and
Daniel Shu Wei Ting +9 more
openaire +5 more sources
Cracking the genetic code with neural networks
Frontiers in Artificial Intelligence, 2023 The genetic code is textbook scientific knowledge that was soundly established without resorting to Artificial Intelligence (AI). The goal of our study was to check whether a neural network could re-discover, on its own, the mapping links between codons ...
Marc Joiret +8 more
doaj +1 more source