Neurocomputing
Overview
Neurocomputing is a renowned interdisciplinary journal that focuses on the intersection of neuroscience and artificial intelligence. It publishes cutting-edge research on computational models, algorithms, and applications related to neural networks, machine learning, and cognitive systems. With a broad scope, Neurocomputing serves as a platform for scientists and engineers to explore the latest advancements in understanding and simulating the brain's computational capabilities.
Details
Details
Abbr.
Neurocomputing (Amst)
Start
1989
End
Continuing
Frequency
Bimonthly
p-ISSN
0925-2312
e-ISSN
1872-8286
Country
Netherlands
Language
English
Metrics
Metrics
h-index / Ranks: 754
196
SJR / Ranks: 1413
1815
CiteScore / Ranks: 1211
10.80
JIF / Ranks: 1121
6.0
Recent Articles
1.
Xie J, Yan Y, Saxena A, Qiu Q, Chen J, Sun H, et al.
Neurocomputing (Amst)
. 2025 Jan;
611.
PMID: 39802630
Inference using deep neural networks on mobile devices has been an active area of research in recent years. The design of a deep learning inference framework targeted for mobile devices...
2.
Xu J
Neurocomputing (Amst)
. 2024 Apr;
583.
PMID: 38645687
The area under the Receiver Operating Characteristic (ROC) curve (AUC) is a standard metric for quantifying and comparing binary classifiers. Real world applications often require classification into multiple (more than...
3.
Ma L, Liang L
Neurocomputing (Amst)
. 2023 Aug;
551.
PMID: 37587916
Adversarial training is the most popular and general strategy to improve Deep Neural Network (DNN) robustness against adversarial noises. Many adversarial training methods have been proposed in the past few...
4.
Wu J, Guo D, Wang L, Yang S, Zheng Y, Shapey J, et al.
Neurocomputing (Amst)
. 2023 Aug;
544:None.
PMID: 37528990
Accurate segmentation of brain tumors from medical images is important for diagnosis and treatment planning, and it often requires multi-modal or contrast-enhanced images. However, in practice some modalities of a...
5.
Salehi A, Balasubramanian M
Neurocomputing (Amst)
. 2023 Jun;
523:116-129.
PMID: 37332394
Dense pixel matching problems such as optical flow and disparity estimation are among the most challenging tasks in computer vision. Recently, several deep learning methods designed for these problems have...
6.
Zhang J, Zheng N, Liu M, Yao D, Wang Y, Wang J, et al.
Neurocomputing (Amst)
. 2023 Mar;
534:161-170.
PMID: 36923265
The mutant strains of COVID-19 caused a global explosion of infections, including many cities of China. In 2020, a hybrid AI model was proposed by Zheng et al., which accurately...
7.
Zgheib R, Chahbandarian G, Kamalov F, Messiry H, Al-Gindy A
Neurocomputing (Amst)
. 2023 Jan;
528:160-177.
PMID: 36647510
The connection between humans and digital technologies has been documented extensively in the past decades but needs to be evaluated through the current global pandemic. Artificial Intelligence(AI), with its two...
8.
Ge Y, Liu H, Du J, Li Z, Wei Y
Neurocomputing (Amst)
. 2022 Nov;
518:496-506.
PMID: 36341142
With the global outbreak of COVID-19, wearing face masks has been actively introduced as an effective public measure to reduce the risk of virus infection. This measure leads to the...
9.
Kamalov F, Rajab K, Cherukuri A, Elnagar A, Safaraliev M
Neurocomputing (Amst)
. 2022 Sep;
511:142-154.
PMID: 36097509
The Covid-19 pandemic has galvanized scientists to apply machine learning methods to help combat the crisis. Despite the significant amount of research there exists no comprehensive survey devoted specifically to...
10.
Zhang Y, Su L, Liu Z, Tan W, Jiang Y, Cheng C
Neurocomputing (Amst)
. 2022 Jun;
503:314-324.
PMID: 35765410
COVID-19 has spread rapidly all over the world and has infected more than 200 countries and regions. Early screening of suspected infected patients is essential for preventing and combating COVID-19....