International Journal of Machine Learning and Cybernetics

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Computational reasoning based on complemented distributive lattices
International Journal of Machine Learning and Cybernetics - Tập 6 Số 3 - Trang 475-478 - 2015
Jiang Shu-Rong, Jin‐Xiao Mi, Lei Ma
Value of foreknowledge in the online k-taxi problem
International Journal of Machine Learning and Cybernetics - - 2017
Xin Zheng, Ke Wang, Weimin Ma
A novel consensus model with probabilistic linguistic preference relation for the utilization mode selection of renewable energy sources
International Journal of Machine Learning and Cybernetics - Tập 14 Số 5 - Trang 1845-1861 - 2023
Xinli You, Fujun Hou
Normal neutrosophic frank aggregation operators and their application in multi-attribute group decision making
International Journal of Machine Learning and Cybernetics - Tập 10 - Trang 833-852 - 2017
Peide Liu, Peng Wang, Junlin Liu
Normal neutrosophic set (NNS) can conveniently express random and fuzzy information, and Frank operators have the properties of generalization and flexibility. In this paper, we will extend Frank operators to Normal neutrosophic numbers (NNNs), and propose some Frank aggregation Operators for NNNs, then develop two new decision methods with NNNs. Firstly, based on Frank operators, the operational ...... hiện toàn bộ
Face sketch-photo recognition using local gradient checksum: LGCS
International Journal of Machine Learning and Cybernetics - Tập 8 Số 5 - Trang 1457-1469 - 2017
Hiranmoy Roy, Debotosh Bhattacharjee
Brain tumor segmentation based on region of interest-aided localization and segmentation U-Net
International Journal of Machine Learning and Cybernetics - Tập 13 - Trang 2435-2445 - 2022
Shidong Li, Jianwei Liu, Zhanjie Song
Since magnetic resonance imaging (MRI) has superior soft tissue contrast, contouring (brain) tumor accurately by MRI images is essential in medical image processing. Segmenting tumor accurately is immensely challenging, since tumor and normal tissues are often inextricably intertwined in the brain. It is also extremely time consuming manually. Late deep learning techniques start to show reasonable...... hiện toàn bộ
Discernible neighborhood counting based incremental feature selection for heterogeneous data
International Journal of Machine Learning and Cybernetics - Tập 11 - Trang 1115-1127 - 2019
Yanyan Yang, Shiji Song, Degang Chen, Xiao Zhang
Incremental feature selection refreshes a subset of information-rich features from added-in samples without forgetting the previously learned knowledge. However, most existing algorithms for incremental feature selection have no explicit mechanisms to handle heterogeneous data with symbolic and real-valued features. Therefore, this paper presents an incremental feature selection method for heterog...... hiện toàn bộ
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
Xiaowei Zhang, Ruoxia Li, Chao Han, Rong Yao
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
Personalized federated learning based on multi-head attention algorithm
International Journal of Machine Learning and Cybernetics - Tập 14 - Trang 3783-3798 - 2023
Shanshan Jiang, Meixia Lu, Kai Hu, Jiasheng Wu, Yaogen Li, Liguo Weng, Min Xia, Haifeng Lin
Federated Learning (FL) is an algorithm for the encrypted exchange of model parameters while ensuring the independence of participants. Classic federated learning does not take into account the correlation between features, nor does it take into account the data differences caused by the reasonable personalization of each client. Therefore, this paper proposes a personalized federated learning alg...... hiện toàn bộ
Detection and localization of crowd behavior using a novel tracklet-based model
International Journal of Machine Learning and Cybernetics - Tập 9 - Trang 1999-2010 - 2017
Hamidreza Rabiee, Hossein Mousavi, Moin Nabi, Mahdyar Ravanbakhsh
In this paper, two novel descriptors are introduced to detect and localize abnormal behaviors in crowded scenes. The first proposed descriptor is based on the orientation and magnitude of short trajectories extracted by tracking interest points in spatio-temporal 3D patches. The proposed descriptor employs a novel simplified Histogram of Oriented Tracklets (sHOT), which is shown to be very effecti...... hiện toàn bộ
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