International Journal of Machine Learning and Cybernetics
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Unsupervised image-to-image translation using intra-domain reconstruction loss
International Journal of Machine Learning and Cybernetics - - 2020
Robust stability analysis of uncertain genetic regulatory networks with mixed time delays
International Journal of Machine Learning and Cybernetics - Tập 7 - Trang 1005-1022 - 2014
This study is concerned with the robust stability problem of uncertain genetic regulatory networks (GRNs) with random discrete time delays and distributed time delays which exist both in translation process and feedback regulation process. By utilizing a novel Lyapunov–Krasovskii functional which contains some triple integral terms and takes into account the ranges of delays, we derive sufficient ...... hiện toàn bộ
Robust semi-supervised spatial picture fuzzy clustering with local membership and KL-divergence for image segmentation
International Journal of Machine Learning and Cybernetics - Tập 13 - Trang 963-987 - 2021
Aiming at existing symmetric regularized picture fuzzy clustering with weak robustness, and it is difficult to meet the need for image segmentation in the presence of high noise. Hence, a robust dynamic semi-supervised symmetric regularized picture fuzzy clustering with KL-divergence and spatial information constraints is presented in this paper. Firstly, a weighted squared Euclidean distance from...... hiện toàn bộ
PEN-DS: progressive enhancement network based on detail supplementation for low-light image enhancement
International Journal of Machine Learning and Cybernetics - - Trang 1-16 - 2023
Images captured in low-light environments suffer from severe degradation, which can be unfavorable for human observation and subsequent computer vision tasks. Although many enhancement methods based on deep learning have been proposed, the obtained enhancement images still suffer from drawbacks such as color distortion, noise, and blur. To solve these problems, we propose a progressive enhancement...... hiện toàn bộ
Incremental approaches to knowledge reduction based on characteristic matrices
International Journal of Machine Learning and Cybernetics - Tập 8 - Trang 203-222 - 2014
Knowledge reduction is complicated with the dynamic change of the object set in applications. In this paper, we propose incremental approaches to computing the type-1 and type-2 characteristic matrices of coverings with respect to variation of objects. Also we present two incremental algorithms of calculating the second and sixth lower and upper approximations of sets when adding and deleting more...... hiện toàn bộ
Fuzzy clustering with non-local information for image segmentation
International Journal of Machine Learning and Cybernetics - Tập 5 - Trang 845-859 - 2014
Fuzzy c-means (FCM) algorithms have been shown effective for image segmentation. A series of enhanced FCM algorithms incorporating spatial information have been developed for reducing the effect of noises. This paper presents a robust FCM algorithm with non-local spatial information for image segmentation, termed as NLFCM. It incorporates two factors: one is the local similarity measure depending ...... hiện toàn bộ
A context-aware semantic modeling framework for efficient image retrieval
International Journal of Machine Learning and Cybernetics - Tập 8 - Trang 1259-1285 - 2016
In recent years, high-level image representation is gaining popularity in image classification and retrieval tasks. This paper proposes an efficient scheme known as semantic context model to derive high-level image descriptors well suited for the retrieval operation. Semantic context model uses an undirected graphical model based formulation which jointly exploits low-level visual features and con...... hiện toàn bộ
Using a small dataset to classify strength-interactions with an elastic display: a case study for the screening of autism spectrum disorder
International Journal of Machine Learning and Cybernetics - Tập 14 - Trang 151-169 - 2022
Health data collection of children with autism spectrum disorder (ASD) is challenging, time-consuming, and expensive; thus, working with small datasets is inevitable in this area. The diagnosis rate in ASD is low, leading to several challenges, including imbalance classes, potential overfitting, and sampling bias, making it difficult to show its potential in real-life situations. This paper presen...... hiện toàn bộ
Semi-supervised classification with privileged information
International Journal of Machine Learning and Cybernetics - Tập 6 - Trang 667-676 - 2015
The privileged information that is available only for the training examples and not available for test examples, is a new concept proposed by Vapnik and Vashist (Neural Netw 22(5–6):544–557, 2009). With the help of the privileged information, learning using privileged information (LUPI) (Neural Netw 22(5–6):544–557, 2009) can significantly accelerate the speed of learning. However, LUPI is a stand...... hiện toàn bộ
Robust image watermarking scheme in lifting wavelet domain using GA-LSVR hybridization
International Journal of Machine Learning and Cybernetics - Tập 9 - Trang 145-161 - 2015
This paper presents an imperceptible, robust, secure and efficient image watermarking scheme in lifting wavelet domain using combination of genetic algorithm (GA) and Lagrangian support vector regression (LSVR). First, four subbands low–low (LL), low–high (LH), high–low (HL) and high–high (HH) are obtained by decomposing the host image from spatial domain to frequency domain using one level liftin...... hiện toàn bộ
Tổng số: 1,453
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