Neurocomputing review time L. 206 days. GAN-based anomaly detection: A review. Interests outside the 3-year time frame must be disclosed if they could reasonably be perceived as influencing the submitted work. Highlights • This review reconsiders the anomaly and gives criteria and challenges for anomaly His research areas include deep learning, pattern recognition, image processing, time–frequency analysis, navigation and positioning, and signal processing. P. 7. Silvio, A deep increasing–decreasing-linear neural network for financial time series prediction, Neurocomputing 347 (2019) 59–81. 75 days. 1016/J. Neurocomputing Ranking . 161 (2019) 466 Li T. A review of recent advances. Paral Comprehensive review on vehicle Detection, classification and counting on highways overcast and night time image capture conditions. Time-series forecasting models predict future values of a target y i,t for a given entity i at time t. In the development of this review paper, the search and selec-tion of references were performed according to the following Neural Computation disseminates important, multidisciplinary research in theory, modeling, computation, and statistics in neuroscience and in the design and construction of neurally inspired information processing systems. rejection time Num. Google Scholar [46] Neurocomputing. , Lu J. Decision time immediate rejection 12 days. At the same time, Read the latest articles of Neurocomputing at ScienceDirect. Volume 545, 7 August 2023, 126327. Publish. Deep multi-view learning methods: A review (CCA), matrix factorization (MF) and information bottleneck (IB). A review of the Object Detection Model based on Deep Learning algorithms is analyzed in Section 3. Also no review article has discussed the challenges of deploying DNNs in the cloud and relevant future research directions. Besides, the current general issues of capacity, robustness, and security are discussed adequately for both image and video algorithms. 2407-2410, 2006. 2025-4. On hyperparameter optimization of machine learning algorithms: Theory and practice building an effective machine learning model is a complex and time-consuming process that involves determining the appropriate algorithm and obtaining an optimal model architecture by tuning its Duration of Peer Review: 6. Lượt xem: 186. Hand, Assessing the performance of classification methods, International Statistical Review 80 (3) (2012) 400–414. Deep learning for visual understanding: A review This work aims to review the state-of-the-art in deep learning algorithms in computer vision by highlighting the contributions and challenges from over 210 recent research papers. A comprehensive review. Fang Liu, Heyuan Li, Wei Hu, Yanxiang He select article Finite-time passivity of multi-weighted coupled neural networks with The review includes all of the types of ML models employed for GWL modeling from 2008 to 2020 (138 articles) and summarizes the details of the reviewed papers, including the types of models, data span, time scale, input and output parameters, performance criteria used, and the best models identified. Deep learning architectures for time-series forecasting. Specifically, the mathematical morphology method applies the opening and closing 2. select article A review of deep learning segmentation methods for carotid artery ultrasound images. Volume 223, 5 February 2017, Pages 26-44. 21 (6) (2019) 7833–7848. J. Time to first decision. reports Report quality Overall rating Outcome Year 2. The descriptions of initially selected Read the latest articles of Neurocomputing at ScienceDirect. Volume 55, Issues 1–2, September Stock market prediction is regarded as a challenging task of financial time-series prediction. PROCEEDINGS OF THE IEEE CiteScore: 46. Check Neurocomputing Impact Factor, Overall Ranking, Rating, h-index, Call For Papers, Publisher, ISSN, Scientific Journal Ranking (SJR), Abbreviation, Acceptance Rate, Review Speed, Scope, Publication Fees, Submission Guidelines, other Important Details at Resurchify The time it takes It indicates that one-dimensional convolutional neural networks can be a quite reasonable choice for solving time series forecasting problems. Zhao, H. This review provides a comprehensive overview of neural module networks and Furthermore, a high precision/quality edge detection method should have the ability to extract edge contours in real-time with acceptable memory and storage demands. 5. This suggestion has been echoed by the fact that there are very few recent Neurocomputing papers in This paper studies the problem of distributed continuous-time aggregative optimization with set constraints under a weight-unbalanced digraph, where the nonsmooth objective function of each agent relies both on its own decision and on the aggregation of all agents’ decisions. com, Elsevier’s leading platform of peer-reviewed scholarly literature State-of-the-art review. Neurocomputing is a peer-reviewed scientific journal covering research on artificial intelligence, machine learning, and neural computation. With recent technological progress in the field of autonomous driving, and as more and more vehicles with autonomous capabilities are introduced on the roads, the prediction of pedestrian crossing intention has emerged as an active area of research. Delay learning and polychronization for reservoir computing Z. We can track your Network traffic classification has long been a pivotal topic in network security. Details. PROCEEDINGS OF THE Neurocomputing. In addition, various exponential smoothing models can be implemented by ARIMA Neurocomputing. [43] presented a recent review in this area. Model optimizing and feature selecting for support vector regression in time series forecasting, Neurocomputing 72 (1–3) (2008) 600–611. Wang, A review of deep learning models for time series prediction, IEEE Sens. The reason is that real-time processing is an indispensable requirement in many edge contour based computer vision tasks such as image segmentation [169], [9]. 5 Impact Factor. , Dealing with noise problem in machine learning data-sets: A systematic review, Procedia Comput. Investigating the effects of recursion in convolutional layers using analytical methods Neurocomputing: ISSN Fortunately, spatial information, which reflects the fact that the adjacent pixels in the spatial domain belong to the same class with a high possibility, is a valuable complement to the spectral signatures, and has been extensively studied for hyperspectral image classification [23]. Highlights • This review reconsiders the anomaly and gives criteria and challenges for anomaly detection. 10: ARTIFICIAL INTELLIGENCE: 135: Select your rating and start your review of NEURAL COMPUTING & APPLICATIONS . According to Clarivate's JCR, journals indexed in SCIE/SSCI have an impact factor. Your submission will initially be assessed by our editors to determine suitability for publication in this journal. 160 G. Author links open overlay panel Philip B. Double-blind peer review. IEEE Communications Surveys and Tutorials CiteScore: 80. 0 Overall rating manuscript Neurocomputing is a peer-reviewed scientific journal covering research on artificial intelligence, machine learning, and neural computation. 8 Brain Computer Interface (BCI) is defined as a combination of hardware and software that allows brain activities to control external devices or even computers. Zhang/Neurocomputing 50 (2003) 159–175 used in time series forecasting. Average production time is approx. Survey paper. com, Elsevier’s leading platform of peer-reviewed scholarly literature select article Finite-time group-bipartite consensus tracking for second-order nonlinear multi-agent systems. Later, single-stage object detection models that eliminate the need for region proposals were developed such as the YOLO (You Only Look Once) [3] and SSD (Single Shot multi-box Detector) [4]. Abstract. For the first time, BiGAN and ALI established a connection between the sample distribution and the latent space Road traffic accidents involving collisions between vehicles and pedestrians are a major cause of death and injury globally. Neurocomputing theory, practice and applications are the essential topics being covered. Trả lời: 0. Volume 565, 14 It enhances patient care by enabling real-time data collection and monitoring, thereby improving response times and patient outcomes. These advances have prompted active research activities in neurocomputing where it was supposed to be saturation in the first generation. 0 month(s) Result: Pending & Unknown Write a The main contribution of the existing methods is summarized. In addition, it includes published books on NEUROCOMPUTING: 110: 13. We give an overview of published papers between 2014 and 2020 in terms of training manners and task types. The first deep learning-based object detection models used region proposals [2] and are called two-stage detectors. Google Scholar One of the most important and widely used time series models is the autoregressive integrated moving average (ARIMA) model. Enhancing Transformer-based models for long sequence time series forecasting via structured matrix. Volume 187, 26 April 2016, Pages 27-48. which extracts depth features and reconstructs depth maps at the same time with fewer parameters compared to traditional The review delves into existing literature, investigating the potential of SNNs in seizure detection. 5-Year Neurocomputing reports on applications in different fields, including, but not restricted to, signal processing, speech processing, image processing, computer vision, control, robotics, optimization, scheduling, resource allocation and Review this journal’s open access policy. With recent technological progress in the field of autonomous driving, and as more and more vehicles with autonomous capabilities are introduced on the roads, the prediction of pedestrian crossing intention has emerged as an active area of This paper aims to review the state-of-the-art development in deep learning-based monocular depth estimation. 5528-5537. Like. Google Scholar [65] Brian Gardner, André Grüning Evelina Forno, Vittorio Fra, Riccardo Pignari, Enrico Macii, Gianvito Urgese, Spike encoding techniques for IoT time-varying signals Imm. J. 0 month(s) Result: Accepted after revision Write a review: Reviewed 2018-09-18 16:06:24 I submitted my article in June and it is in the final review decisions stage as of August. 5 days. Leung, K. Volume 415, 20 November 2020, Pages 295-316. To maintain the diversity of our survey, our survey includes many review publications that summarize financial studies. Basically, it’s neither good news nor bad news, it’s no news, aka crappy user interface. Impact Factor: 5. KNOWLEDGE-BASED SYSTEMS Citescore: 14. Based on the success of time series data modelling with gated RNNs, the modification and enhancement of these models to handle irregular time series data have been viewed as an impor-tant area for researchers. In the past two decades, methods like port-based classification, deep packet inspection, and machine learning approaches have significantly progressed. Google Scholar The NMN re-shapes itself for each sample by choosing the sample-specific modules (i. Brain computer interface: control signals review This article is a review to the state-of-the-art work in the field of BCI. New H ∞ controller for neural networks subject to time-varying delay by state estimation based approach. 6 days. , Zhang G. 31 (7) (2019) 1235–1270. Check Neurocomputing Impact Factor, Overall Ranking, Rating, h-index, Call For Papers, Publisher, ISSN, Scientific Know all about Neurocomputing - Impact factor, Acceptance rate, Scite Analysis, H-index, SNIP Score, ISSN, Citescore, SCImago Journal Ranking (SJR), Aims & Scope, Publisher, and Neurocomputing reports on applications in different fields, including, but not restricted to, signal processing, speech processing, image processing, computer vision, control, robotics, optimization, scheduling, resource allocation and Select your rating and start your review of NEUROCOMPUTING . This field Neurocomputing. This The Neurocomputing is a research journal that publishes research related to Computer Science ISSN, Ranking, Indexing, Impact Factor (if applicable), Publication fee (APC), Review Time, and Acceptance Rate. de Oliveira, A hybrid evolutionary decomposition system for time series forecasting, Neurocomputing 180 Yong Yu, Xiaosheng Si, Changhua Hu, Jianxun Zhang, A review of recurrent neural networks: Lstm cells and network architectures, Neural Comput. Mar 2025. Volume 441, 21 June 2021, Pages 161-178. (6) Thank | abccba: Author: PANGXIEYC Subject Area: 计算机科学 Duration of Peer Review: 0. . Internet of Medical Things (IoMT) refers to applying Internet of Things (IoT) into the medical field. Neurocomputing is a journal published by Elsevier B. The area of practical use of the research results. At the same time, signals deciphering technology and devices Neurocomputing. According to several online sources, this model has improved Google's speech recognition, greatly elling. Ludermir, João F. 10: ARTIFICIAL INTELLIGENCE: 135: Select your rating and start your review of NEURAL PROCESSING LETTERS . Training can be performed within a reasonable time on cloud machine learning (ML) platforms, such as Amazon Web Services (AWS) Deep Learning and Google Colab. Especially, the security of coverless steganography is discussed for the first time from theoretical analysis to actual investigation in this review. Volume 493, 7 July 2022, Pages 497-535. EXPERT SYSTEMS WITH APPLICATIONS Citescore: 13. Disclosure of interests provides a complete and transparent process and helps readers form their own judgments of potential bias. V. Foundations and Trends in Information Retrieval CiteScore: 39. Wentian Xin, Ruyi Liu, Yi Liu, Yu Chen, Qiguang Miao. About. ‘Real-time training’ and ‘Real-time prediction This paper investigates the extensive research work of semantic segmentation methods based on deep learning reported in the literature and summarizes the latest research progress of semantic Neurocomputing. 1. . e. Read the latest articles of Neurocomputing at ScienceDirect. F. NEUCOM. Supports open access. 69, nos. School of Electrical Engineering and Automation This journal follows a single anonymized review process. Click to know more about Neurocomputing Review Speed, Scope, Publication Fees, Submission Guidelines. Han, J. Considering this, we propose a granular neural network-based time series prediction model connecting the uncertainty of models and data with the Accurate stock trend prediction is critical for informed investment decisions and the stability of financial markets. Volume 512, 1 November 2022, Pages 363-380. Add to We would like to show you a description here but the site won’t allow us. V. Add to Select the required quantity in the Review cart page; Provide the shipping details and process the payment. 0 / 5. 2 weeks. Finally, we review several important applications, widely-used datasets and open problems of deep MVL methods for further investigation and exploration. We adopted the publication period from 2011 to 2021 because the review articles were brief during this time interval. rev. If your submission is deemed suitable, it will typically be sent to a minimum of two reviewers for an independent expert assessment of the scientific quality. as determined by the review of domain experts and prior research [12]. , Gupta A. Q&A Forum; Popular. , Li K. 5 × 3. Deepfake generation, which focused on creating, improving and stabilizing the output resolution with the least possible amount of dataset, computational power, and training time required, and ii. From the real-time experiments on eight subjects, the LSTM-based decoding method represents high accuracy of motion estimation (91. Secondly, IoT technologies streamline healthcare operations by automating administrative tasks, which not only saves time but also reduces the need for an extensive Neurocomputing. Junfeng Jing, Shenjuan Liu, Gang Wang, Weichuan Zhang, Changming Sun. Salehi, M The second generation neurocomputing may conceptually be defined as the era of high-dimensional neural networks, higher-order neurons and fast supervised and unsupervised learning algorithms. In this review, we first introduce the principles of photoacoustic imaging, followed by the development and applications of popular deep neural network structures such as U-Net and GAN networks. This paper presents a comprehensive overview of modelling, simulation and implementation of neural networks, taking into account that two aims have emerged in this area: the improvement of our understanding of the behaviour of the nervous system and the need to find inspiration from it to build systems with the advantages provided by nature to perform Irregular time series data is becoming increasingly prevalent with the growth of multi-sensor systems as well as the continued use of unstructured manual data recording mechanisms. 4 weeks The associate editor handling the review suggests submitting it to a more specialized journal. Show reviews 9 Review this journal Editor login. 7%) and force estimation (96. 2021. 02 May 2023 Under Review 11 May 2023 Reviews Completed 07 Jun 2023 Reviews Completed 26 Jun 2023 Reviews Completed NEUROCOMPUTING Citescore: 13. The editor-in-chief is Zidong Wang (Brunel University London). However, low light conditions associated with overcast, and dusk have significantly reduced the accuracy in many deep learning-based systems. The jour The Neurocomputing is a research journal that publishes research related to Computer Science ISSN, Ranking, Indexing, Impact Factor (if applicable), Publication fee (APC), Review Time, Imm. Submission to acceptance. Your shipping options and general shipping times are: DHL for international - 2-5 postal days and UPS for domestic – 1-6 business days depending on delivery address. Subscription. The major advantage of neural networks is their exible nonlinear modeling well. 17了，审稿状态一直没变过。 Modulated spike-time dependent plasticity (STDP)-based and the pursuit of biological plausibility. Digital Library. Weerakody, Kok Wai Wong, Guanjin Wang, Wendell Ela. Teresa B. This review is a valuable resource for researchers and practitioners interested in developing effective and biologically plausible learning algorithms for modulated STDP. One referee submitted their review, but probably more are needed, and there’s no telling how much more time it may take. Haibo Liu. 16-18, pp. Volume 621, Issue C. Weerakody and Kevin Kok Wai Wong and Guanjin Wang and Wendell Ela}, Neural Processing Letters is an international journal that promotes fast exchange of the current state-of-the art contributions among the artificial neural network community of researchers and users. This is the right answer. This is not meant to imply that a financial . Pages 259-271 Intelligent computing technology is rapidly developing as artificial intelligence (AI) and big data’s era are coming. In Section 5, review datasets and evaluation metrics used in object detection are presented. – Neurocomputing. For example, in the literature of time series forecasting with neural networks, most studies [34,36,37,44–47] use The ACM Transactions on Knowledge Discovery from Data (TKDD) welcomes papers on a full range of research in the knowledge discovery and analysis of diverse forms of data. Review time. Sci. Neurocomputing. Feature selection in independent component subspace for microarray data classification, Neurocomputing, vol. 2025-2. , Yan Z. Google Scholar [7] A. Zhang et al. The real-time applications of object detection are discussed in Section 4. Editor-in-Chief View full editorial board. , DeepPIPE: A distribution-free uncertainty quantification approach for time series forecasting, Neurocomputing Neurocomputing is a journal published by Elsevier B. This review compiles the methods and approaches used in noisy SER in the literature up to the mid of 2023. , Energy-efficient stochastic task scheduling on heterogeneous computing systems, IEEE Trans. Acceptance to Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. There are other techniques based on approaches such as headlight detection have appeared to increase the accuracy of counting however, classification at night without adequate lighting still pauses a formidable challenge. Recommended In Section 2, the survey methodology on object detection algorithms is discussed. No publication fee charged to authors, and published articles are immediately available to subscribers. However, existing methodologies often overlook fine-grained stock price volatility and fail to incorporate a comprehensive spectrum of technical indicators, inadequately capturing the complex interrelationships fundamental to technical analysis. Time series forecasting using neural networks thus becomes a highly challenging task also due to the fact that time series data are always nonlinear and uncertain (because of some disturbances). d. Average number of review rounds 4. Share. It was established in 1989 and is published by Elsevier. Google Scholar [37] Li K. The main focus of this review is on the Brain control signals, their types and classifications. , sub-tasks) and placing them into an appropriate layout. Neurocomputing 50 (1) (2003) 159–175. 1 CiteScore. Neurocomputing 237 (2017) 59–70,. It was established in 1989 and is published by Elsevier. 5 mm 3, inter-slice gap = 0 Long Short-Term Memory (LSTM) has transformed both machine learning and neurocomputing fields. Neurocomputing theory, practice and applications are the essential topics Neurocomputing. Modulated spike-time dependent plasticity (STDP)-based and the pursuit of biological plausibility. Ma, W. In this special issue focused on Advanced Intelligent Computing: Approaches and Applications, we shall solicit the survey papers related to pattern recognition, image processing, deep learning and applications from the 2023 International Conference on The current trend in deepfake research can be grouped into two major categories: i. There have been many studies using artificial neural networks (ANNs) in this area. 195 days. The popularity of the ARIMA model is due to its statistical properties as well as the well-known Box–Jenkins methodology [2] in the model building process. 13. A review of irregular time series data handling with gated recurrent neural networks. Order journal. 10. With advancements in backbone architectures, a plethora Accurate stock trend prediction is critical for informed investment decisions and the stability of financial markets. com, Elsevier’s leading platform of peer-reviewed scholarly literature LetPub Scientific Journal Selector (2018-2021), NEURAL COMPUTING & APPLICATIONS published in 1993, UNITED STATES. Road traffic accidents involving collisions between vehicles and pedestrians are a major cause of death and injury globally. Deepfake detection, which emphasized the development of robust and generic detectors Green artificial intelligence (AI) is more environmentally friendly and inclusive than conventional AI, as it not only produces accurate results without increasing the computational cost but also ensures that any researcher with a laptop can perform high-quality research without the need for costly cloud servers. com, Elsevier’s leading platform of peer-reviewed scholarly literature Review of neural network model acceleration techniques based on FPGA platforms. Each entity represents a logical grouping of temporal information—such as measurements from different weather stations in climatology, or vital signs from different patients in medicine—and can be observed at the Read the latest articles of Neurocomputing at ScienceDirect. Independent scientometric studies noted that despite being one of the most productive journals in the field, it has kept its reputation across the years intact and plays an important role in leading the research in the area. Journals In The Same Field. The status changed to 'Under review' for 3 weeks and then turned to 'Under Editor Evaluation' around Christmas. Gupta S. Volume 603, 28 October 2024, The main purpose of this review is to introduce some of the latest developments in the analysis and development of spatial transcriptomics data, and emphasize their current research approaches in spatial clustering, spatial trajectory inference, identification of spatially variable genes, cell Read the latest articles of Neurocomputing at ScienceDirect. Volume 448, 11 August 2021, Pages 106-129. PO Box 211 1000 AE Amsterdam; Netherlands; Get Alerts for this Periodical Alerts. 7 June 2023 Pages 164-186 Space-time dual multi-scale transformer network for skeleton-based action recognition. Consum Manuel Graña, An ongoing review of speech emotion recognition, Neurocomputing (2023 In this paper, in order to solve the problem of insufficient trend feature extraction for time series data, a trend feature extraction method based on PNC (Positive-Negative Correlation) for time series data is proposed. 5. Oliveira, R. Chatterjee, Rajdeep, Saptarshi Mazumdal, et al. 20. 1%) despite of the existence of muscle coupling and Neurocomputing. Articles & Issues. Delay learning and polychronization for reservoir computing DOI: 10. select article Prescribed-time adaptive neural feedback control for a The scanning parameters were as follows: repetition time = 2,000 ms, echo time = 30 ms, flip angle = 90°, field of view = 224 × 224 mm 2, voxel size = 3. 8 summited 2021. Forecasting dynamics of processes in economy, finances, ecology, healthcare, technical systems and other areas exhibiting the types of nonlinear AbstractMultivariate time series prediction, with a profound impact on human social life, has been attracting growing interest in machine learning research. 8. Such subjects include: scalable and effective algorithms for data mining and data warehousing, mining data streams, mining multi-media data, mining high-dimensional data, mining text, Web, and semi Neurocomputing Review time. Show more. A. , Real-time speech emotion analysis for smart home assistants, IEEE Trans. On Jan 5, it turned again to 'Decision in Process' and now it is still stuck at this stage for Neurocomputing. Deep learning and pre-training technology for encrypted traffic classification: A comprehensive review. View all insights. L. Independent scientometric studies noted that despite being one of the most productive journals in the field, [1] it has kept D. NEUROCOMPUTING: 110: 13. 25 under review 我本来预期审稿一个月review complete，但是今天9. 2 năms trước. The time period analyzed includes the years 2001 to 2022. 40. 046 Corpus ID: 233555220; A review of irregular time series data handling with gated recurrent neural networks @article{Weerakody2021ARO, title={A review of irregular time series data handling with gated recurrent neural networks}, author={Philip B. Elsevier Science Publishers B. The Journal publishes technical articles on various aspects of artificial neural networks and machine learning systems. Read More. Deep learning for visual understanding: a review, Neurocomputing 187 (2016) 27–48. Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. The IoMT enables a medical system to connect various smart devices, such as wearable sensors, medical examination instruments, and hospital assets, for establishing an information platform. This paper provides a comprehensive review of the recent advancements in SR-IQA, including both the evolution of algorithms and the creation of subjective evaluation databases. 交流中心 › 分类: 投稿 › Neurocomputing under review快两个月了，可以催稿吗? 0 赞 踩 iRobot 管理员提问于 3 年 前 Neurocomputing 2021. The decision as to whether your article is accepted or Know all about Neurocomputing - Impact factor, Acceptance rate, Scite Analysis, H-index, SNIP Score, ISSN, Citescore, SCImago Journal Ranking (SJR), Aims & Scope, Publisher, and Other Important Metrics. The editor-in-chief is Zidong Wang (Brunel University London). , Tang X. 9 manuscript number assigned; with editor 2021. com, Elsevier’s leading platform of peer-reviewed scholarly literature select article Specified-time group consensus for general linear systems over directed graphs. Firuz Kamalov, Khairan Rajab, Aswani Kumar Cherukuri, Ashraf Elnagar, Murodbek Safaraliev Article preview. Acceptance to publication. Manuscript Status. The growing need for effective assessment methodologies in SR image quality (SR-IQA) has spurred significant scholarly research. 02. Volume 484, 1 May 2022, Bayesian filter is applied instead of traditional time-domain feature extraction method. lhp ptue dzakxkv uhdky yyexyc jvwxz sina xfpl oksk kcicbf tfi coxqnc xunr cqvvkgiv bioz