Browse by Journal

Number of items: 26.

Ghozzi, Yosr and Hamdani, Tarek M and Hagras, Hani and Ouahada, Khmaies and Chabchoub, Habib and Alimi, Adel M (2024) A deep learning based interval type-2 fuzzy approach for image retrieval systems. Neurocomputing, 603. p. 128251. DOI https://doi.org/10.1016/j.neucom.2024.128251

Fumanal-Idocin, Javier and Andreu-Perez, Javier (2024) Ex-Fuzzy: A library for symbolic explainable AI through fuzzy logic programming. Neurocomputing, 599. p. 128048. DOI https://doi.org/10.1016/j.neucom.2024.128048

Xia, Tian and Sun, Xia and Yang, Yidong and Long, Yunfei and Sutcliffe, Richard (2024) A dual relation-encoder network for aspect sentiment triplet extraction. Neurocomputing, 597. p. 128064. DOI https://doi.org/10.1016/j.neucom.2024.128064

Ramos-Cruz, Bruno and Andreu-Perez, Javier and Martínez, Luis (2024) The cybersecurity mesh: A comprehensive survey of involved artificial intelligence methods, cryptographic protocols and challenges for future research. Neurocomputing, 581. p. 127427. DOI https://doi.org/10.1016/j.neucom.2024.127427

Amorim, Renato and Makarenkov, Vladimir (2023) On k-means iterations and Gaussian clusters. Neurocomputing, 553. p. 126547. DOI https://doi.org/10.1016/j.neucom.2023.126547

K. Gupta, Prashant and Andreu-Perez, Javier (2022) A Gentle Introduction and Survey on Computing with Words (CWW) Methodologies. Neurocomputing, 500. pp. 921-937. DOI https://doi.org/10.1016/j.neucom.2022.05.097

Zhuang, Mingxi and Zhong, Xunyu and Gu, Dongbing and Feng, Liying and Zhong, Xungao and Hu, Huosheng (2021) LRDNet: A lightweight and efficient network with refined dual attention decorder for real-time semantic segmentation. Neurocomputing, 459. pp. 349-360. DOI https://doi.org/10.1016/j.neucom.2021.07.019

Yi, Dewei and Su, Jinya and Chen, Wen-Hua (2021) Probabilistic Faster R-CNN with Stochastic Region Proposing: Towards Object Detection and Recognition in Remote Sensing Imagery. Neurocomputing, 459. pp. 290-301. DOI https://doi.org/10.1016/j.neucom.2021.06.072

Hu, Jingzhao and Wang, Chen and Jia, Qiaomei and Bu, Qirong and Sutcliffe, Richard and Feng, Jun (2021) ScalingNet: Extracting features from raw EEG data for emotion recognition. Neurocomputing, 463. pp. 177-184. DOI https://doi.org/10.1016/j.neucom.2021.08.018

Zeng, Yuejie and Xiao, Lin and Li, Kenli and Li, Jichun and Li, Keqin and Jian, Zhen (2020) Design and analysis of three nonlinearly activated ZNN models for solving time-varying linear matrix inequalities in finite time. Neurocomputing, 390. pp. 78-87. DOI https://doi.org/10.1016/j.neucom.2020.01.070

Andreu-Perez, Javier (2020) Fuzzy learning and its applications in neural-engineering. Neurocomputing, 389. pp. 196-197. DOI https://doi.org/10.1016/j.neucom.2019.03.071

Akshansh, Gupta and R. K., Agrawal and Jyoti Singh, Kirar and Baljeet, Kaur and Weiping, Ding and Chin-Teng, Lin and Andreu-Perez, Javier and Mukesh, Prasad (2020) A Hierarchical Meta-model for Multi-Class Mental Task Based Brain-Computer Interfaces. Neurocomputing, 389. pp. 207-217. DOI https://doi.org/10.1016/j.neucom.2018.07.094

Ju, Zhaojie and Liu, Jinguo and Huang, Yong An and Kubota, Naoyuki and Gan, John Q (2020) Neural Networks and Learning Systems for Human Machine Interfacing. Neurocomputing, 390. pp. 196-197. DOI https://doi.org/10.1016/j.neucom.2019.10.058

Yang, Delong and Zhong, Xunyu and Gu, Dongbing and Peng, Xiafu and Hu, Huosheng (2020) Unsupervised framework for depth estimation and camera motion prediction from video. Neurocomputing, 385. pp. 169-185. DOI https://doi.org/10.1016/j.neucom.2019.12.049

Raza, Haider and Rathee, Dheeraj and Zhou, Shang-Ming and Cecotti, Hubert and Prasad, Girijesh (2019) Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface. Neurocomputing, 343. pp. 154-166. DOI https://doi.org/10.1016/j.neucom.2018.04.087

González, Jesús and Ortega, Julio and Damas, Miguel and Martín-Smith, Pedro and Gan, John Q (2019) A new multi-objective wrapper method for feature selection – Accuracy and stability analysis for BCI. Neurocomputing, 333. pp. 407-418. DOI https://doi.org/10.1016/j.neucom.2019.01.017

Ferdous, Moshina M and Bao, Yanchun and Vinciotti, Veronica and Liu, Xiaohui and Wilson, Paul (2018) Predicting gene expression from genome wide protein binding profiles. Neurocomputing, 275. pp. 1490-1499. DOI https://doi.org/10.1016/j.neucom.2017.09.094

Martín-Smith, Pedro and Ortega, Julio and Asensio-Cubero, Javier and Gan, John Q and Ortiz, Andrés (2017) A supervised filter method for multi-objective feature selection in EEG classification based on multi-resolution analysis for BCI. Neurocomputing, 250. pp. 45-56. DOI https://doi.org/10.1016/j.neucom.2016.09.123

Ameri, Rasool and Pouyan, Ali and Abolghasemi, Vahid (2016) Projective dictionary pair learning for EEG signal classification in brain computer interface applications. Neurocomputing, 218. pp. 382-389. DOI https://doi.org/10.1016/j.neucom.2016.08.082

Amorim, RC and Makarenkov, V (2016) Applying subclustering and Lp distance in Weighted K-Means with distributed centroids. Neurocomputing, 173 (P3). pp. 700-707. DOI https://doi.org/10.1016/j.neucom.2015.08.018

Zhou, Huiyu and Gu, Dongbing and Wang, Ling and Fei, Minrui (2016) Editorial: Special issue: Life system modeling and simulation. Neurocomputing, 174. pp. 454-455. DOI https://doi.org/10.1016/j.neucom.2015.08.064

Deng, Li and Lu, Gen and Shao, Yuying and Fei, Minrui and Hu, Huosheng (2016) A novel camera calibration technique based on differential evolution particle swarm optimization algorithm. Neurocomputing, 174. pp. 456-465. DOI https://doi.org/10.1016/j.neucom.2015.03.119

Li, Junhua and Struzik, Zbigniew and Zhang, Liqing and Cichocki, Andrzej (2015) Feature learning from incomplete EEG with denoising autoencoder. Neurocomputing, 165. pp. 23-31. DOI https://doi.org/10.1016/j.neucom.2014.08.092

Duro, João A and Kumar Saxena, Dhish and Deb, Kalyanmoy and Zhang, Qingfu (2014) Machine learning based decision support for many-objective optimization problems. Neurocomputing, 146. pp. 30-47. DOI https://doi.org/10.1016/j.neucom.2014.06.076

Vella, Vince and Ng, Wing Lon (2014) Enhancing risk-adjusted performance of stock market intraday trading with Neuro-Fuzzy systems. Neurocomputing, 141. pp. 170-187. DOI https://doi.org/10.1016/j.neucom.2014.03.026

Wang, Pu and Tang, Ke and Weise, Thomas and Tsang, EPK and Yao, Xin (2014) Multiobjective genetic programming for maximizing ROC performance. Neurocomputing, 125. pp. 102-118. DOI https://doi.org/10.1016/j.neucom.2012.06.054

This list was generated on Mon May 5 21:58:04 2025 BST.