Results 121 to 130 of about 9,662,134 (136)

Modulation of horizontal cell receptive fields in the light adapted goldfish retina

, 1996
Jan Verweij, Maarten Kamermans, E. C. Van den Aker, Henk Spekreijse   +3 more
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Models of receptive-field dynamics in visual cortex

, 1999
GEORGE KALARICKAL, JONATHAN MARSHALL
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Center surround receptive field structure of cone bipolar cells in primate retina

, 2000
Dennis M. Dacey, Orin Packer, Lisa C. Diller, David H. Brainard, Beth Peterson, Barry Lee   +5 more
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Primary afferents with multiple receptive fields in rat colon and stomach

, 2000
H. R. Berthoud, Penny A. Lynn, L. Ashley Blackshaw   +2 more
openalex   +1 more source

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Multi-Receptive-Field CNN for Semantic Segmentation of Medical Images

IEEE journal of biomedical and health informatics, 2020
The context-based convolutional neural network (CNN) is one of the most well-known CNNs to improve the performance of semantic segmentation. It has achieved remarkable success in various medical image segmentation tasks.
Liangliang Liu, Fangxiang Wu, Yu-Ping Wang, Jianxin Wang   +3 more
semanticscholar   +1 more source

Dynamic Receptive Field Generation for Full-Reference Image Quality Assessment

IEEE Transactions on Image Processing, 2020
Most full-reference image quality assessment (FR-IQA) methods advanced to date have been holistically designed without regard to the type of distortion impairing the image. However, the perception of distortion depends nonlinearly on the distortion type.
Woojae Kim, Anh-Duc Nguyen, Sanghoon Lee, A. Bovik   +3 more
semanticscholar   +1 more source

InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction

Information Processing in Medical Imaging, 2019
Geometric deep learning provides a principled and versatile manner for integration of imaging and non-imaging modalities in the medical domain. Graph Convolutional Networks (GCNs) in particular have been explored on a wide variety of problems such as ...
Anees Kazi, Shayan Shekarforoush, S. Krishna, Hendrik Burwinkel, G. Vivar, K. Kortüm, Seyed-Ahmad Ahmadi, Shadi Albarqouni, N. Navab   +8 more
semanticscholar   +1 more source

Multireceptive Field Graph Convolutional Networks for Machine Fault Diagnosis

IEEE transactions on industrial electronics (1982. Print), 2021
Deep learning (DL) based methods have swept the field of mechanical fault diagnosis, because of the powerful ability of feature representation. However, many of existing DL methods fail in relationship mining between signals explicitly. Unlike those deep
Tianfu Li, Zhibin Zhao, Chuang Sun, Ruqiang Yan, Xuefeng Chen   +4 more
semanticscholar   +1 more source

Stimulus specific responses from beyond the classical receptive field: neurophysiological mechanisms for local-global comparisons in visual neurons.

Annual Review of Neuroscience, 1985
We perceive the visual world as a unitary whole, yet one of the guiding principles of nearly a half century of neurophysiological research since the early recordings by Hartline (1938) has been that the visual system consists of neurons that are driven ...
J. Allman, F. Miezin, E. McGuinness
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Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields

European Conference on Computer Vision, 2018
Recently, in the community of Neural Style Transfer, several algorithms are proposed to transfer an artistic style in real-time, which is known as Fast Style Transfer.
Yongcheng Jing, Yang Liu, Yezhou Yang, Zunlei Feng, Yizhou Yu, Mingli Song   +5 more
semanticscholar   +1 more source