{"title":"利用具有关注机制的多尺度扩张登森网的创新型乳腺癌检测框架","authors":"Subhashini Ramachandran, Rajasekar Velusamy, Namakkal Venkataraman Srinivasan Sree Rathna Lakshmi, Chakaravarthi Sivanandam","doi":"10.1080/0954898x.2024.2343348","DOIUrl":null,"url":null,"abstract":"Cancer-related deadly diseases affect both developed and underdeveloped nations worldwide. Effective network learning is crucial to more reliably identify and categorize breast carcinoma in vast an...","PeriodicalId":54735,"journal":{"name":"Network-Computation in Neural Systems","volume":"6 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An innovative breast cancer detection framework using multiscale dilated densenet with attention mechanism\",\"authors\":\"Subhashini Ramachandran, Rajasekar Velusamy, Namakkal Venkataraman Srinivasan Sree Rathna Lakshmi, Chakaravarthi Sivanandam\",\"doi\":\"10.1080/0954898x.2024.2343348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cancer-related deadly diseases affect both developed and underdeveloped nations worldwide. Effective network learning is crucial to more reliably identify and categorize breast carcinoma in vast an...\",\"PeriodicalId\":54735,\"journal\":{\"name\":\"Network-Computation in Neural Systems\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Network-Computation in Neural Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1080/0954898x.2024.2343348\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Network-Computation in Neural Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/0954898x.2024.2343348","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
An innovative breast cancer detection framework using multiscale dilated densenet with attention mechanism
Cancer-related deadly diseases affect both developed and underdeveloped nations worldwide. Effective network learning is crucial to more reliably identify and categorize breast carcinoma in vast an...
期刊介绍：
Network: Computation in Neural Systems welcomes submissions of research papers that integrate theoretical neuroscience with experimental data, emphasizing the utilization of cutting-edge technologies. We invite authors and researchers to contribute their work in the following areas:
Theoretical Neuroscience: This section encompasses neural network modeling approaches that elucidate brain function.
Neural Networks in Data Analysis and Pattern Recognition: We encourage submissions exploring the use of neural networks for data analysis and pattern recognition, including but not limited to image analysis and speech processing applications.
Neural Networks in Control Systems: This category encompasses the utilization of neural networks in control systems, including robotics, state estimation, fault detection, and diagnosis.
Analysis of Neurophysiological Data: We invite submissions focusing on the analysis of neurophysiology data obtained from experimental studies involving animals.
Analysis of Experimental Data on the Human Brain: This section includes papers analyzing experimental data from studies on the human brain, utilizing imaging techniques such as MRI, fMRI, EEG, and PET.
Neurobiological Foundations of Consciousness: We encourage submissions exploring the neural bases of consciousness in the brain and its simulation in machines.
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