Results 21 to 30 of about 136,861 (303)

Unsupervised learning of generative topic saliency for person re-identification [PDF]

, 2014
(c) 2014. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.© 2014. The copyright of this document resides with its authors.
Wang, H, Hanxiao Wang, Tao Xiang, Shaogang Gong, Xiang, T, Gong, S   +5 more
core   +1 more source

DeConFuse: a deep convolutional transform-based unsupervised fusion framework

EURASIP Journal on Advances in Signal Processing, 2020
This work proposes an unsupervised fusion framework based on deep convolutional transform learning. The great learning ability of convolutional filters for data analysis is well acknowledged.
Pooja Gupta, Jyoti Maggu, Angshul Majumdar, Emilie Chouzenoux, Giovanni Chierchia   +4 more
doaj   +1 more source

Unsupervised Learning of Edges [PDF]

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Camera ready version for CVPR ...
Yin Li 0003, Manohar Paluri, James M. Rehg, Piotr Dollár   +3 more
openaire   +2 more sources

Unsupervised learning of overlapping image components using divisive input modulation [PDF]

, 2009
This paper demonstrates that nonnegative matrix factorisation is mathematically related to a class of neural networks that employ negative feedback as a mechanism of competition. This observation inspires a novel learning algorithm which we call Divisive
De Meyer, Kris, Spratling, Michael, Kompass, R., de Meyer, K., Spratling, M.W., Kompass, R   +5 more
core   +1 more source

ResNet Autoencoders for Unsupervised Feature Learning From High-Dimensional Data: Deep Models Resistant to Performance Degradation

IEEE Access, 2021
Efficient modeling of high-dimensional data requires extracting only relevant dimensions through feature learning. Unsupervised feature learning has gained tremendous attention due to its unbiased approach, no need for prior knowledge or expensive manual
Chathurika S. Wickramasinghe, Daniel L. Marino, Milos Manic   +2 more
doaj   +1 more source

ClassCut for Unsupervised Class Segmentation [PDF]

, 2010
We propose a novel method for unsupervised class segmentation on a set of images. It alternates between segmenting object instances and learning a class model.
Bogdan Alexe, Vittorio Ferrari, Alexe, Bogdan, Deselaers, Thomas, Ferrari, Vittorio, Thomas Deselaers   +5 more
core   +1 more source

Meta-Unsupervised-Learning: A supervised approach to unsupervised learning

CoRR, 2016
22 ...
Vikas K. Garg 0001, Adam Tauman Kalai
openaire   +2 more sources

Breast Image Classification Based on Multi-feature Joint Supervised Dictionary Learning [PDF]

Jisuanji gongcheng, 2018
Aiming at the problem that the unsupervised dictionary learning algorithm has low image classification accuracy,a supervised dictionary learning classification algorithm which combines with multiple image features is proposed.It uses the convolution ...
LIU Lihui,XU Jun,GONG Lei
doaj   +1 more source

Learning from Multiple Instances: A Two-Stage Unsupervised Image Denoising Framework Based on Deep Image Prior

Applied Sciences, 2022
Supervised image denoising methods based on deep neural networks require a large amount of noisy-clean or noisy image pairs for network training. Thus, their performance drops drastically when the given noisy image is significantly different from the ...
Shaoping Xu, Xiaojun Chen, Yiling Tang, Shunliang Jiang, Xiaohui Cheng, Nan Xiao   +5 more
doaj   +1 more source

Memristor Neural Network Training with Clock Synchronous Neuromorphic System

Micromachines, 2019
Memristor devices are considered to have the potential to implement unsupervised learning, especially spike timing-dependent plasticity (STDP), in the field of neuromorphic hardware research.
Sumin Jo, Wookyung Sun, Bokyung Kim, Sunhee Kim, Junhee Park, Hyungsoon Shin   +5 more
doaj   +1 more source