Proceedings of the IEEE最新文献_第4页

Next-Generation Multiple Access 下一代多址接入

IF 23.2 1区计算机科学

Proceedings of the IEEE Pub Date : 2024-12-09 DOI: 10.1109/JPROC.2024.3493572

Yuanwei Liu;Zhiguo Ding;Robert Schober

引用次数: 0

Domain Generalization for Medical Image Analysis: A Review 医学图像分析领域概化研究进展

IF 23.2 1区计算机科学

Proceedings of the IEEE Pub Date : 2024-12-05 DOI: 10.1109/JPROC.2024.3507831

Jee Seok Yoon;Kwanseok Oh;Yooseung Shin;Maciej A. Mazurowski;Heung-Il Suk

{"title":"Domain Generalization for Medical Image Analysis: A Review","authors":"Jee Seok Yoon;Kwanseok Oh;Yooseung Shin;Maciej A. Mazurowski;Heung-Il Suk","doi":"10.1109/JPROC.2024.3507831","DOIUrl":"10.1109/JPROC.2024.3507831","url":null,"abstract":"Medical image analysis (MedIA) has become an essential tool in medicine and healthcare, aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in deep learning (DL) have made significant contributions to its advances. However, deploying DL models for MedIA in real-world situations remains challenging due to their failure to generalize across the distributional gap between training and testing samples—a problem known as domain shift. Researchers have dedicated their efforts to developing various DL methods to adapt and perform robustly on unknown and out-of-distribution (OOD) data distributions. This article comprehensively reviews domain generalization (DG) studies specifically tailored for MedIA. We provide a holistic view of how DG techniques interact within the broader MedIA system, going beyond methodologies to consider the operational implications on the entire MedIA workflow. Specifically, we categorize DG methods into data-level, feature-level, model-level, and analysis-level methods. We show how those methods can be used in various stages of the MedIA workflow with DL equipped from data acquisition to model prediction and analysis. Furthermore, we critically analyze the strengths and weaknesses of various methods, unveiling future research opportunities.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 10","pages":"1583-1609"},"PeriodicalIF":23.2,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142782597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NOMA as the Next-Generation Multiple Access in Nonterrestrial Networks 新一代非地面网络多址接入技术

IF 23.2 1区计算机科学

Proceedings of the IEEE Pub Date : 2024-11-27 DOI: 10.1109/JPROC.2024.3496775

Baha Eddine Youcef Belmekki;Mohamed-Slim Alouini

{"title":"NOMA as the Next-Generation Multiple Access in Nonterrestrial Networks","authors":"Baha Eddine Youcef Belmekki;Mohamed-Slim Alouini","doi":"10.1109/JPROC.2024.3496775","DOIUrl":"10.1109/JPROC.2024.3496775","url":null,"abstract":"Nonterrestrial networks (NTN) are pivotal, enabling technologies for achieving global and ubiquitous connectivity in the sixth generation (6G) of wireless systems. On the other hand, nonorthogonal multiple access (NOMA) emerges as a promising candidate for the next-generation multiple access (NGMA), designed to enable massive connectivity and improve spectral efficiency. In this article, we investigate the synergy between NTN and NOMA [power-domain NOMA (PD-NOMA)], which are integral in addressing the connectivity challenges of 6G. First, we present an overview of NTN, detailing their types, unique characteristics, and the challenges they face. Then, we explain the foundational principles of NOMA, such as power allocation and access strategies. We, then, argue the suitability of NOMA as an NGMA technology for 6G and how it addresses the specific challenges associated with NTN. Furthermore, we explore the integration and the interplay of NTN and NOMA with emerging technologies such as millimeter-wave (mmWave), terahertz (THz) frequencies, reconfigurable intelligent surfaces (RISs), and integrated sensing and communication (ISAC) systems. These advancements are critical in meeting the 6G requirements for extremely high data rates and improved spectral efficiency, enhancing the overall functionality of NTN and NOMA. We, then, examine how NTN using NOMA can use different architectural frameworks, including cellular, cell-free (CF), ad hoc, and integrated access and backhaul (IAB) systems, and detailed several use cases where the integration of NTN and NOMA could have a significant impact, such as in vehicular communications, the Internet of Things (IoT), urban air mobility (UAM), and achieving global connectivity. To optimize NTN using NOMA, we present a comprehensive overview of the mathematical optimization algorithms and machine learning tools. Finally, we elaborate on the primary challenges associated with merging NTN with NOMA and propose relevant future research avenues.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 9","pages":"1303-1345"},"PeriodicalIF":23.2,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Membership IEEE 会员

IF 23.2 1区计算机科学

Proceedings of the IEEE Pub Date : 2024-11-08 DOI: 10.1109/JPROC.2024.3479437

引用次数: 0

Future Special Issues/Special Sections of the Proceedings 论文集》未来的特刊/专栏

IF 23.2 1区计算机科学

Proceedings of the IEEE Pub Date : 2024-11-08 DOI: 10.1109/JPROC.2024.3479435

引用次数: 0

Joint Source–Channel Coding: Fundamentals and Recent Progress in Practical Designs 源-信道联合编码：实用设计的基本原理和最新进展

IF 20.6 1区计算机科学

Proceedings of the IEEE Pub Date : 2024-11-08 DOI: 10.1109/jproc.2024.3477331