Results 11 to 20 of about 1,525,474 (355)
IET Biometrics, 2022 Breast cancer accounts for the largest number of patients among all cancers in the world. Intervention treatment for early breast cancer can dramatically extend a woman's 5‐year survival rate.
Lilei Sun +6 more
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Two‐view attention‐guided convolutional neural network for mammographic image classification
CAAI Transactions on Intelligence Technology, 2023 Deep learning has been widely used in the field of mammographic image classification owing to its superiority in automatic feature extraction. However, general deep learning models cannot achieve very satisfactory classification results on mammographic ...
Lilei Sun +6 more
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Few-parameter learning for a hierarchical perceptual grouping system
Mathematical Biosciences and Engineering, 2023 Perceptual grouping along well-established Gestalt laws provides one set of traditional methods that provide a tiny set of meaningful parameters to be adjusted for each application field. More complex and challenging tasks require a hierarchical setting,
Eckart Michaelsen
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An Introduction to Object Recognition [PDF]
Zeitschrift für Naturforschung C, 1998 Abstract In this report we present a general introduction to object recognition. We begin with brief discussions of the terminology used in the object recognition literature and the psychophysi cal tasks that are used to investigate object recognition. We then discuss models of shape representation. We dispense with the idea that shape
Liter, J., Bülthoff, H.
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Journal of Open Archaeology Data, 2021 These data were used to build an object detection model to locate Relict Charcoal Hearths (RCH) as described in the paper “When Computers Dream of Charcoal: Using Deep Learning, Open Tools and Open Data to Identify Relict Charcoal Hearths in and around ...
Weston Conner +2 more
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Multiview-Learning-Based Generic Palmprint Recognition: A Literature Review
Mathematics, 2023 Palmprint recognition has been widely applied to security authentication due to its rich characteristics, i.e., local direction, wrinkle, and texture.
Shuping Zhao, Lunke Fei, Jie Wen
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Object Recognition with and without Objects [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 While recent deep neural networks have achieved a promising performance on object recognition, they rely implicitly on the visual contents of the whole image. In this paper, we train deep neural networks on the foreground (object) and background (context) regions of images respectively.
Lingxi Xie, Zhuotun Zhu, Alan L. Yuille
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Some Reiteration Theorems for R, L, RR, RL, LR, and LL Limiting Interpolation Spaces
Journal of Function Spaces, 2021 We consider the K-interpolation methods involving slowly varying functions. We establish some reiteration formulae including so-called L or R limiting interpolation spaces as well as the RR, RL, LR, and LL extremal interpolation spaces.
Leo R. Ya. Doktorski
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CGENet: A Deep Graph Model for COVID-19 Detection Based on Chest CT
Biology, 2021 Accurate and timely diagnosis of COVID-19 is indispensable to control its spread. This study proposes a novel explainable COVID-19 diagnosis system called CGENet based on graph embedding and an extreme learning machine for chest CT images. We put forward
Si-Yuan Lu +3 more
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Spatiotemporal neural dynamics of object recognition under uncertainty in humans
eLife, 2023 While there is a wealth of knowledge about core object recognition—our ability to recognize clear, high-contrast object images—how the brain accomplishes object recognition tasks under increased uncertainty remains poorly understood.
Yuan-hao Wu, Ella Podvalny, Biyu J He
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