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Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IBISML, IPSJ-CVIM 2024-03-03
15:00		 Hiroshima Hiroshima Univ. Higashi-Hiroshima campus
(Primary: On-site, Secondary: Online)		 Learning VQ-VAE for Image Dimensionality Reduction with Spatial Frequency Loss
Naoyuki Ichimura (AIST) PRMU2023-60		 Vector Quantized-Variational AutoEncoders (VQ-VAEs) are a type of deep neural networks designed to learn an approximate ... [more] PRMU2023-60
pp.53-58
PRMU, IPSJ-CVIM 2021-03-04
10:30		 Online Online Learning Convolutional Neural Networks with Spatial Frequency Loss
Naoyuki Ichimura (AIST) PRMU2020-73		 The pixel-wise L2 and pixel-wise L1 losses have been commonly used to measure the consistency between images in learning... [more] PRMU2020-73
pp.25-30
PRMU, BioX 2018-03-18
11:10		 Tokyo   Learning Convolutional Autoencoders Using a Loss Function Based on Spatial Frequencies and Colors
Naoyuki Ichimura (AIST) BioX2017-36 PRMU2017-172		 This paper presents a learning method for convolutional autoencoders (CAEs) for extracting features from images. CAEs ca... [more] BioX2017-36 PRMU2017-172
pp.1-6
PRMU 2009-06-19
09:20		 Hokkaido Hokkaido Univ. Matching with Local Invariant Features Based on Dense Edge Sampling
Naoyuki Ichimura (AIST) PRMU2009-51		 Detecting local regions in which descriptors are computed is necessary
to extract local invariant features for image ma... [more]		 PRMU2009-51
pp.71-76
PRMU, MVE 2008-11-28
15:40		 Osaka Osaka Univ. Extracting Local Invariant Features Using the Approximated LoG Filter -- A GPU-based Implementation --
Naoyuki Ichimura (AIST) PRMU2008-144 MVE2008-93		  [more] PRMU2008-144 MVE2008-93
pp.243-250
PRMU, IE 2008-03-11
15:25		 Ishikawa  
Naoyuki Ichimura (AIST) IE2007-330 PRMU2007-314		 Detecting local regions is necessary to extract local invariant
features for image matching. The detection can be perfo... [more]		 IE2007-330 PRMU2007-314
pp.449-456
 Results 1 - 6 of 6  /   
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