Network (Bristol, England)最新文献

CNN filter sizes, effects, limitations, and challenges: An exploratory study. CNN过滤器的大小、效果、限制和挑战：一项探索性研究。

Network (Bristol, England) Pub Date : 2025-07-20 DOI: 10.1080/0954898X.2025.2533865

Mohamed Aboukhair, Fahad Alsheref, Adel Assiri, Abdelrahim Koura, Mohammed Kayed

{"title":"CNN filter sizes, effects, limitations, and challenges: An exploratory study.","authors":"Mohamed Aboukhair, Fahad Alsheref, Adel Assiri, Abdelrahim Koura, Mohammed Kayed","doi":"10.1080/0954898X.2025.2533865","DOIUrl":"https://doi.org/10.1080/0954898X.2025.2533865","url":null,"abstract":"This study explores the impacts of filter sizes on convolutional neural networks (CNNs) models, moving away from the common belief that small filters (3x3) give better results. The goal is to highlight the potential of large filters and encourage researchers to investigate their capabilities. The usage of large filters will increase the computational power which leads common researchers to reduce the filter size to reserve this power; however, other researchers address the potential of large filters to enhance the performance of CNN models. Currently, there are few pure CNN models that achieve optimal performance with large filters showing how far the large filter sizes topic is not addressed well by the community. As the availability of computer power and image sizes increase, traditional obstacles that hinder researchers from using large filter sizes will gradually diminish. This paper guides researchers by analysing and exploring the limitations, challenges, and impacts of CNN filter sizes on different CNN architectures. This will help utilize large filters' distinctive opportunities and potential. To our knowledge, we find four opportunities from utilizing large filters. A comprehensive comparison of researches on different CNN architectures shows a bias for small filters (3x3) and the possible potential of large filters.","PeriodicalId":520718,"journal":{"name":"Network (Bristol, England)","volume":" ","pages":"1-29"},"PeriodicalIF":0.0,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid optimization with constraints handling for combinatorial test case prioritization problems. 组合测试用例优先级问题的约束处理混合优化。

Network (Bristol, England) Pub Date : 2025-07-10 DOI: 10.1080/0954898X.2025.2517130

Selvakumar J, Sudhir Sharma, Mukesh Kumar Tripathi

{"title":"Hybrid optimization with constraints handling for combinatorial test case prioritization problems.","authors":"Selvakumar J, Sudhir Sharma, Mukesh Kumar Tripathi","doi":"10.1080/0954898X.2025.2517130","DOIUrl":"https://doi.org/10.1080/0954898X.2025.2517130","url":null,"abstract":"In software development, software testing is very crucial for developing good quality software, where the effectiveness of software is to be tested. For software testing, test suites and test cases need to be prepared in minimum execution time with the test case prioritization (TCP) problems. Generally, some of the researchers mainly focus on the constraint problems, such as time and fault on TCP. In this research, the novel Fractional Hybrid Leader Based Optimization (FHLO) is introduced with constraint handling for combinatorial TCP. To detect faults earlier, the TCP is an important technique as it reduces the regression testing cost and prioritizes the test case execution. Based on the detected fault and branch coverage, the priority of the test case for program execution is decided. Furthermore, the FHLO algorithm establishes the TCP for detecting the program fault, which prioritizes the test case, and relies on maximum values of Average Percentage of Branch Coverage (APBC) and Average Percentage of Fault Detected (APFD). From the analysis, the devised FHLO algorithm attains a maximum value of 0.966 for APFD and 0.888 for APBC.","PeriodicalId":520718,"journal":{"name":"Network (Bristol, England)","volume":" ","pages":"1-31"},"PeriodicalIF":0.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gradient energy valley optimization enabled segmentation and Spinal VGG-16 Net for brain tumour detection. 梯度能谷优化使分割和脊髓VGG-16网络脑肿瘤检测。

Network (Bristol, England) Pub Date : 2025-06-23 DOI: 10.1080/0954898X.2025.2513690

Kishore Bhamidipati, G Anuradha, Satish Muppidi, S Anjali Devi

{"title":"Gradient energy valley optimization enabled segmentation and Spinal VGG-16 Net for brain tumour detection.","authors":"Kishore Bhamidipati, G Anuradha, Satish Muppidi, S Anjali Devi","doi":"10.1080/0954898X.2025.2513690","DOIUrl":"10.1080/0954898X.2025.2513690","url":null,"abstract":"The anomalous enlargement of brain cells is known as Brain Tumour (BT), which can cause serious damage to different blood vessel and nerve in human body. A precise and early detection of BT is foremost important to eliminate severe illness. Thus, a SpinalNet Visual Geometry Group-16 (Spinal VGG-16-Net) is introduced for early BT detection. At first, Magnetic Resonance Imaging (MRI) of image obtained from data sample is subjected to image denoising by bilateral filter. Then, BT area is segmented from the image using entropy-based Kapur thresholding technique, where threshold values are ideally selected by Gradient Energy Valley Optimization (GEVO), which is designed by incorporating Energy Valley Optimization (EVO) with Stochastic Gradient Descent (SGD) algorithm. Then, process of image augmentation is worked and later, feature extraction is performed to mine the most significant features. Finally, BT is detected using proposed Spinal VGG-16Net, which is devised by combining both SpinalNet and VGG-16 Net. The Spinal VGG-16-Net is compared with some of the existing schemes, and it attained maximum accuracy of 92.14%, True Positive Rate (TPR) of 93.16%, True Negative Rate (TNR) of 91.35%, Negative Predictive Value (NPV) 89.73%, and Positive Predictive Value (PPV) o of 92.13%.","PeriodicalId":520718,"journal":{"name":"Network (Bristol, England)","volume":" ","pages":"1-35"},"PeriodicalIF":0.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144370074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A smoothing gradient-based neural network strategy for solving semidefinite programming problems. 求解半定规划问题的平滑梯度神经网络策略。

IF 7.8

Network (Bristol, England) Pub Date : 2022-08-01 Epub Date: 2022-08-04 DOI: 10.1080/0954898X.2022.2104463

Asiye Nikseresht, Alireza Nazemi

引用次数: 0

Semantic segmentation of human cell nucleus using deep U-Net and other versions of U-Net models. 基于深度U-Net和其他版本U-Net模型的人类细胞核语义分割。

IF 7.8

Network (Bristol, England) Pub Date : 2022-08-01 Epub Date: 2022-07-12 DOI: 10.1080/0954898X.2022.2096938

Yadavendra, Satish Chand

{"title":"Semantic segmentation of human cell nucleus using deep U-Net and other versions of U-Net models.","authors":"Yadavendra, Satish Chand","doi":"10.1080/0954898X.2022.2096938","DOIUrl":"https://doi.org/10.1080/0954898X.2022.2096938","url":null,"abstract":"The deep learning models play an essential role in many areas, including medical image analysis. These models extract important features without human intervention. In this paper, we propose a deep convolution neural network, named as deep U-Net model, for the segmentation of the cell nucleus, a critical functional unit that determines the function and structure of the body. The nucleus contains all kinds of DNA, RNA, chromosomes, and genes governing all life activities, and its disorder may lead to different types of diseases such as cancer, heart disease, diabetes, Alzheimer's, etc. If the nucleus structure is known correctly, diseases due to nucleus disorder may be detected early. It may also reduce the drug discovery time if the shape and size of the nucleus are known. We evaluate the performance of the proposed models on the nucleus segmentation data set used by the Data Science Bowl 2018 competition hosted by Kaggle. We compare its performance with that of the U-Net, Attention U-Net, R2U-Net, Attention R2U-Net, and both versions of the U-Net++ with and without supervision, in terms of loss, dice coefficient, dice loss, intersection over union, and accuracy. Our model performs better than the existing models.","PeriodicalId":520718,"journal":{"name":"Network (Bristol, England)","volume":" ","pages":"167-186"},"PeriodicalIF":7.8,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40587974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Extraction of the association rules from artificial neural networks based on the multiobjective optimization. 基于多目标优化的人工神经网络关联规则提取。

IF 7.8

Network (Bristol, England) Pub Date : 2022-08-01 Epub Date: 2022-10-19 DOI: 10.1080/0954898X.2022.2137258

Dounia Yedjour, Hayat Yedjour, Samira Chouraqui

{"title":"Extraction of the association rules from artificial neural networks based on the multiobjective optimization.","authors":"Dounia Yedjour, Hayat Yedjour, Samira Chouraqui","doi":"10.1080/0954898X.2022.2137258","DOIUrl":"https://doi.org/10.1080/0954898X.2022.2137258","url":null,"abstract":"Artificial Neural Network (ANN) is one of the powerful techniques of machine learning. It has shown its effectiveness in both prediction and classification problems. However, in some fields there is still some reticence towards their use mainly the fact that they do not justify their answers. The lack of transparency on how ANN makes decisions motivated us to develop our rule extraction algorithm that extracts comprehensible rules with high accuracy and high fidelity. The aim is to generate a set of rules that mimic the decision of ANN and cover a larger set of patterns. The obtained rule sets should satisfy a well-balanced trade-off between the fidelity, the accuracy and the comprehensibility. The proposed algorithm consists of a three steps: ANN learning phase, rule extraction phase and rule simplification phase. The rule extraction phase is based on the extraction of the association rules while the rules simplification procedure is based on the laws of Boolean algebra. To evaluate the performance of our algorithm, the system has been studied using four datasets, and then compared with other rule extraction methods. The results show that our proposal offers a small set of rules having the highest accuracy and fidelity values.","PeriodicalId":520718,"journal":{"name":"Network (Bristol, England)","volume":" ","pages":"233-252"},"PeriodicalIF":7.8,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40341361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Artists portray human faces with the Fourier statistics of complex natural scenes. 艺术家用复杂自然场景的傅立叶统计来描绘人脸。

IF 7.8

Network (Bristol, England) Pub Date : 2007-09-01 Epub Date: 2007-08-28 DOI: 10.1080/09548980701574496

Christoph Redies, Jan Hänisch, Marko Blickhan, Joachim Denzler

{"title":"Artists portray human faces with the Fourier statistics of complex natural scenes.","authors":"Christoph Redies, Jan Hänisch, Marko Blickhan, Joachim Denzler","doi":"10.1080/09548980701574496","DOIUrl":"https://doi.org/10.1080/09548980701574496","url":null,"abstract":"When artists portray human faces, they generally endow their portraits with properties that render the faces esthetically more pleasing. To obtain insight into the changes introduced by artists, we compared Fourier power spectra in photographs of faces and in portraits by artists. Our analysis was restricted to a large set of monochrome or lightly colored portraits from various Western cultures and revealed a paradoxical result. Although face photographs are not scale-invariant, artists draw human faces with statistical properties that deviate from the face photographs and approximate the scale-invariant, fractal-like properties of complex natural scenes. This result cannot be explained by systematic differences in the complexity of patterns surrounding the faces or by reproduction artifacts. In particular, a moderate change in gamma gradation has little influence on the results. Moreover, the scale-invariant rendering of faces in artists' portraits was found to be independent of cultural variables, such as century of origin or artistic techniques. We suggest that artists have implicit knowledge of image statistics and prefer natural scene statistics (or some other rules associated with them) in their creations. Fractal-like statistics have been demonstrated previously in other forms of visual art and may be a general attribute of esthetic visual stimuli.","PeriodicalId":520718,"journal":{"name":"Network (Bristol, England)","volume":" ","pages":"235-48"},"PeriodicalIF":7.8,"publicationDate":"2007-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09548980701574496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40960593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 58

Estimating sparse spectro-temporal receptive fields with natural stimuli. 用自然刺激估计稀疏的光谱-时间感受野。

IF 7.8

Network (Bristol, England) Pub Date : 2007-09-01 Epub Date: 2007-09-07 DOI: 10.1080/09548980701609235

Stephen V David, Nima Mesgarani, Shihab A Shamma

{"title":"Estimating sparse spectro-temporal receptive fields with natural stimuli.","authors":"Stephen V David, Nima Mesgarani, Shihab A Shamma","doi":"10.1080/09548980701609235","DOIUrl":"https://doi.org/10.1080/09548980701609235","url":null,"abstract":"Several algorithms have been proposed to characterize the spectro-temporal tuning properties of auditory neurons during the presentation of natural stimuli. Algorithms designed to work at realistic signal-to-noise levels must make some prior assumptions about tuning in order to produce accurate fits, and these priors can introduce bias into estimates of tuning. We compare a new, computationally efficient algorithm for estimating tuning properties, boosting, to a more commonly used algorithm, normalized reverse correlation. These algorithms employ the same functional model and cost function, differing only in their priors. We use both algorithms to estimate spectro-temporal tuning properties of neurons in primary auditory cortex during the presentation of continuous human speech. Models estimated using either algorithm, have similar predictive power, although fits by boosting are slightly more accurate. More strikingly, neurons characterized with boosting appear tuned to narrower spectral bandwidths and higher temporal modulation rates than when characterized with normalized reverse correlation. These differences have little impact on responses to speech, which is spectrally broadband and modulated at low rates. However, we find that models estimated by boosting also predict responses to non-speech stimuli more accurately. These findings highlight the crucial role of priors in characterizing neuronal response properties with natural stimuli.","PeriodicalId":520718,"journal":{"name":"Network (Bristol, England)","volume":" ","pages":"191-212"},"PeriodicalIF":7.8,"publicationDate":"2007-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09548980701609235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40960592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 158

Salamander locomotion-induced head movement and retinal motion sensitivity in a correlation-based motion detector model. 基于相关运动检测器模型的蝾螈运动诱导的头部运动和视网膜运动敏感性。

IF 7.8

Network (Bristol, England) Pub Date : 2007-06-01 DOI: 10.1080/09548980701452875

Jeffrey R Begley, Michael A Arbib

引用次数: 0

Complex cell pooling and the statistics of natural images. 复杂的细胞池和自然图像的统计。

IF 7.8

Network (Bristol, England) Pub Date : 2007-06-01 DOI: 10.1080/09548980701418942

Aapo Hyvärinen, Urs Köster

引用次数: 67