Zobrazeno 1 - 10
of 1 518
pro vyhledávání: '"feature aggregation"'
Autor:
Malik Abdul Manan, Jinchao Feng, Muhammad Yaqub, Shahzad Ahmed, Syed Muhammad Ali Imran, Imran Shabir Chuhan, Haroon Ahmed Khan
Publikováno v:
Alexandria Engineering Journal, Vol 105, Iss , Pp 341-359 (2024)
Colorectal polyps are structural abnormalities of the gastrointestinal tract that can potentially become cancerous in some cases. The study introduces a novel framework for colorectal polyp segmentation named the Multi-Scale and Multi-Path Cascaded C
Externí odkaz:
https://doaj.org/article/5762127977b146b288881c9b26273727
Publikováno v:
Heritage Science, Vol 12, Iss 1, Pp 1-20 (2024)
Abstract Semantic segmentation of point cloud data of architectural cultural heritage is of significant importance for HBIM modeling, disease extraction and analysis, and heritage restoration research fields. In the semantic segmentation task of arch
Externí odkaz:
https://doaj.org/article/5919bfe62c794798be727f16b7e73ff9
Autor:
Mingxing Zhang, Jian Xu
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract In transportation, roads sometimes have cracks due to overloading and other reasons, which seriously affect driving safety, and it is crucial to identify and fill road cracks in time. Aiming at the defects of existing semantic segmentation m
Externí odkaz:
https://doaj.org/article/d64b9c87f4c2407895120322d048cbba
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 7, Pp 102150- (2024)
Transformer-based approaches have demonstrated remarkable performance in image processing tasks due to their ability to model long-range dependencies. Current mainstream Transformer-based methods typically confine self-attention computation within wi
Externí odkaz:
https://doaj.org/article/f1b5db6ef4ed4d49a651e95e166b4a51
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 3, Pp 4557-4569 (2024)
Abstract Recently, discriminative and robust identification information has played an increasingly critical role in Person Re-identification (Re-ID). It is a fact that the existing part-based methods demonstrate strong performance in the extraction o
Externí odkaz:
https://doaj.org/article/b1b4f9e5debc48179266cea931b66981
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
The rapid advancement in Earth observation technologies has improved the acquisition of precise data on terrestrial changes. However, traditional binary change detection (BCD) fails to satisfy the complex demands of contemporary applications. In cont
Externí odkaz:
https://doaj.org/article/c5b5cbb4ed3d42f38f12b739efdc61a1
Publikováno v:
IEEE Access, Vol 12, Pp 142542-142554 (2024)
To achieve the interaction between structural and texture information during image restoration, enhance the semantic realism of irregular repairs, and improve restoration performance in cases of large area loss, this paper proposes the Image Restorat
Externí odkaz:
https://doaj.org/article/0877331e563e439f877fa66b85cb5138
Publikováno v:
IEEE Access, Vol 12, Pp 130963-130971 (2024)
Millimeter-wave (MMW) point clouds, characterized by their low resolution and high noise, limit the detection accuracy of point-based IA-SSD method due to the inadequate consideration of contextual information in MMW scenarios. Therefore, this paper
Externí odkaz:
https://doaj.org/article/bcf448e0149846a88d39f3fa0b2ba10d
Autor:
Hongqing Wang, Jun Kit Chaw, Sim Kuan Goh, Liantao Shi, Ting Tin Tin, Nannan Huang, Hong-Seng Gan
Publikováno v:
IEEE Access, Vol 12, Pp 113442-113462 (2024)
Intelligent vehicle detection systems have the potential to improve road safety and optimize traffic management. Despite the continuous advancements in AI technology, the detection of different types of vehicles in complex traffic environments remain
Externí odkaz:
https://doaj.org/article/adbccca419514aa885f2d0d78e562066
Publikováno v:
IEEE Access, Vol 12, Pp 109157-109170 (2024)
Current state-of-the-art sound source localization (SSL) deep learning networks lack feature aggregation within their architecture. Feature aggregation within neural network architectures enhances model performance by enabling the consolidation of in
Externí odkaz:
https://doaj.org/article/91e8ffbe6ab1485493786531262fc315