International journal of wireless communications and network technologies最新文献

Medical Images Analysis Using Deep Learning Technique 利用深度学习技术分析医学影像

International journal of wireless communications and network technologies Pub Date : 2024-01-08 DOI: 10.30534/ijwcnt/2024/021312024

{"title":"Medical Images Analysis Using Deep Learning Technique","authors":"","doi":"10.30534/ijwcnt/2024/021312024","DOIUrl":"https://doi.org/10.30534/ijwcnt/2024/021312024","url":null,"abstract":"Clinical picture classification, pattern recognition, and quantification have seen significant advancements with the help of artificial intelligence, particularly through deep learning techniques. Deep learning has rapidly emerged as the most rapidly evolving field within AI, and its applications have been successfully demonstrated across various domains, including medicine. This review briefly examines recent applied research in several medical fields, such as neurology, brain imaging, retinal analysis, pneumonics, computerized pathology, breast imaging, cardiovascular studies, musculoskeletal imaging, and gastrointestinal imaging. Deep learning networks prove to be highly effective when dealing with large-scale medical datasets, enabling information discovery, knowledge dissemination, and knowledge-based prediction. This research aims to present both foundational knowledge and state-of-the-art deep learning techniques to facilitate the interpretation and analysis of medical images. The primary objectives of this work are to explore advancements in medical image processing research and implement the identified and addressed key criteria in practical applications.","PeriodicalId":470337,"journal":{"name":"International journal of wireless communications and network technologies","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444989","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 Review on Charging Station for E-Vehicle Using Solar with IOT 电动汽车充电站与物联网太阳能技术综述

International journal of wireless communications and network technologies Pub Date : 2024-01-08 DOI: 10.30534/ijwcnt/2024/011312024

引用次数: 0

Diffuse Reflection Imaging for Detection of Surface Defect Based on Machine Learning 基于机器学习的表面缺陷检测漫反射成像技术

International journal of wireless communications and network technologies Pub Date : 2024-01-08 DOI: 10.30534/ijwcnt/2024/031312024

引用次数: 0

Smart Farming For A Greener Tomorrow: The Interflow Of AI, IoT And Robotics 智能农业，绿色明天：人工智能、物联网和机器人技术的相互融合

International journal of wireless communications and network technologies Pub Date : 2024-01-08 DOI: 10.30534/ijwcnt/2024/041312024

引用次数: 0

Wireless Messaging System for Paralysis Patients 瘫痪病人无线信息系统

International journal of wireless communications and network technologies Pub Date : 2023-11-10 DOI: 10.30534/ijwcnt/2023/011262023

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Channel Estimation of MC-CDMA aided with Evolutionary Algorithms 基于进化算法的MC-CDMA信道估计

International journal of wireless communications and network technologies Pub Date : 2023-09-08 DOI: 10.30534/ijwcnt/2023/011252023

引用次数: 0

Review of Load Balancing Algorithms Inspired by Artificial Bee Colony Algorithm in the Cloud Computing 云计算中受人工蜂群算法启发的负载均衡算法综述

International journal of wireless communications and network technologies Pub Date : 2023-09-08 DOI: 10.30534/ijwcnt/2023/021252023

{"title":"Review of Load Balancing Algorithms Inspired by Artificial Bee Colony Algorithm in the Cloud Computing","authors":"","doi":"10.30534/ijwcnt/2023/021252023","DOIUrl":"https://doi.org/10.30534/ijwcnt/2023/021252023","url":null,"abstract":"Research interest in cloud-based load balancing and task scheduling has grown rapidly over the last few years. To be more precise, load balancing of virtual machine tasks (VMs) that require nature-inspired algorithms has become an area of particular interest. It is essential to ensure load balancing between VMs as this avoids overloading and underloading VMs, aspects that can cause issues like high-power consumption, increased execution time, and elevated response times, all of which can ultimately cause a system failure. Swarm intelligence is critical when dealing with issues that are difficult to solve and must be overcome using traditional and mathematical techniques. The algorithm was developed by Karaboga in 2005 and is inspired by the foraging behaviors of an artificial bee colony. This algorithm is extremely robust, convergent, and flexible. Another researcher applied the ABC method to load balancing in order to enhance it. In-depth research on load balancing in cloud computing utilizing the ABC method is presented in this review paper. Moreover, this work also discusses some fundamental ideas on the intelligence and characteristics of the swarm. Additionally, the paper provided a detailed explanation of cloud computing, its services, and components, as well as the concept and objectives of load balancing in the cloud","PeriodicalId":470337,"journal":{"name":"International journal of wireless communications and network technologies","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136362483","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