SEGMENTATION

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Entropy-Bottleneck-Based Privacy Protection Mechanism for Semantic Communication
《Computers, Materials & Continua》2025年第5期2971-2988,共18页Kaiyang Han Xiaoqiang Jia Yangfei Lin Tsutomu Yoshinaga Yalong Li Jiale Wu 
supported in part by the Innovation and Entrepreneurship Training Program for Chinese College Students(No.202410128019);in part by JST ASPIRE Grant Number JPMJAP2325;in part by Support Center for Advanced Telecommunications Technology Research(SCAT).
With the rapid development of artificial intelligence and the Internet of Things,along with the growing demand for privacy-preserving transmission,the need for efficient and secure communication systems has become inc...
关键词：Semantic communication privacy protection semantic segmentation entropy-based compression 
Two-Stage Category-Guided Frequency Modulation for Few-Shot Semantic Segmentation
《Computers, Materials & Continua》2025年第5期1707-1726,共20页Yiming Tang Yanqiu Chen 
Semantic segmentation of novel object categories with limited labeled data remains a challenging problem in computer vision.Few-shot segmentation methods aim to address this problem by recognizing objects from specifi...
关键词：Few-shot semantic segmentation frequency feature category representation 
UltraSegNet:A Hybrid Deep Learning Framework for Enhanced Breast Cancer Segmentation and Classification on Ultrasound Images
《Computers, Materials & Continua》2025年第5期3303-3333,共31页Suhaila Abuowaida Hamza Abu Owida Deema Mohammed Alsekait Nawaf Alshdaifat Diaa Salama Abd Elminaam Mohammad Alshinwan 
funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R435),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
Segmenting a breast ultrasound image is still challenging due to the presence of speckle noise,dependency on the operator,and the variation of image quality.This paper presents the UltraSegNet architecture that addres...
关键词：Breast cancer ultrasound image SEGMENTATION CLASSIFICATION deep learning 
Bilateral Dual-Residual Real-Time Semantic Segmentation Network
《Computers, Materials & Continua》2025年第4期497-515,共19页Shijie Xiang Dong Zhou Dan Tian Zihao Wang 
Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation...
关键词：REAL-TIME residual structure semantic segmentation feature fusion 
CPEWS:Contextual Prototype-Based End-to-End Weakly Supervised Semantic Segmentation
《Computers, Materials & Continua》2025年第4期595-617,共23页Xiaoyan Shao Jiaqi Han Lingling Li Xuezhuan Zhao Jingjing Yan 
funding from the following sources:National Natural Science Foundation of China(U1904119);Research Programs of Henan Science and Technology Department(232102210054);Chongqing Natural Science Foundation(CSTB2023NSCQ-MSX0070);Henan Province Key Research and Development Project(231111212000);Aviation Science Foundation(20230001055002);supported by Henan Center for Outstanding Overseas Scientists(GZS2022011).
The primary challenge in weakly supervised semantic segmentation is effectively leveraging weak annotations while minimizing the performance gap compared to fully supervised methods.End-to-end model designs have gaine...
关键词：End-to-end weakly supervised semantic segmentation vision transformer contextual prototype class activation map 
An Efficient Instance Segmentation Based on Layer Aggregation and Lightweight Convolution
《Computers, Materials & Continua》2025年第4期1041-1055,共15页Hui Jin Shuaiqi Xu Chengyi Duan Ruixue He Ji Zhang 
supported by Science and Technology Research Youth Project of Chongqing Municipal Education Commission(No.KJQN202301104);Cooperative Project between universities in Chongqing and Affiliated Institutes of Chinese Academy of Sciences(No.HZ2021011);Chongqing Municipal Science and Technology Commission Technology Innovation and Application Development Special Project(No.2022TIAD-KPX0040);Action Plan for Quality Development of Chongqing University of Technology Graduate Education(Grant No.gzlcx20242014).
Instance segmentation is crucial in various domains,such as autonomous driving and robotics.However,there is scope for improvement in the detection speed of instance-segmentation algorithms for edge devices.Therefore,...
关键词：Automatic driving CONVOLUTION deep learning real-time instance segmentation 
Segmentation of CAD models using hybrid representation
《虚拟现实与智能硬件(中英文)》2025年第2期188-202,共15页Claude UWIMANA Shengdi ZHOU Limei YANG Zhuqing LI Norbelt MUTAGISHA Edouard NIYONGABO Bin ZHOU 
Supported by the National Key Research and Development Program of China(2024YFB3311703);National Natural Science Foundation of China(61932003);Beijing Science and Technology Plan Project(Z221100006322003).
In this paper,we introduce an innovative method for computer-aided design(CAD)segmentation by concatenating meshes and CAD models.Many previous CAD segmentation methods have achieved impressive performance using singl...
关键词：B-RepNet hybrid segmentation CAD models classification MeshCNN MeshCAD-Net 
MVLA-Net:A Multi-View Lesion Attention Network for Advanced Diagnosis and Grading of Diabetic Retinopathy
《Computers, Materials & Continua》2025年第4期1173-1193,共21页Tariq Mahmood Tanzila Saba Faten S.Alamri Alishba Tahir Noor Ayesha 
funded by Princess Nourah bint Abdulrahman University and Researchers Supporting Project number(PNURSP2025R346);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
Innovation in learning algorithms has made retinal vessel segmentation and automatic grading tech-niques crucial for clinical diagnosis and prevention of diabetic retinopathy.The traditional methods struggle with accu...
关键词：Diabetic retinopathy grading retinal vessel segmentation dual-modal deep learning attention mecha-nism health risks 
Detection of Acute Lymphoblastic Leukemia Using a Novel Bone Marrow Image Segmentation
《Tsinghua Science and Technology》2025年第2期610-623,共14页M.Anline Rejula Ben M Jebin Ravi Selvakumar S.Amutha Eberlein George 
In our study,we present a novel method for automating the segmentation and classification of bone marrow images to distinguish between normal and Acute Lymphoblastic Leukaemia(ALL).Built upon existing segmentation tec...
关键词：Adaptive Neuro-Fuzzy Inference System(ANFIS) blood cells SEGMENTATION leukemia classification 
A Nature-Inspired AI Framework for Accurate Glaucoma Diagnosis
《Computer Modeling in Engineering & Sciences》2025年第4期539-567,共29页Jahanzaib Latif Ahsan Wajahat Alishba Tahir Anas Bilal Mohammed Zakariah Abeer Alnuaim 
Researchers Supporting Project number(RSP2025R314),King Saud University,Riyadh,Saudi Arabia.
Glaucoma,a leading cause of blindness,demands early detection for effective management.While AI-based diagnostic systems are gaining traction,their performance is often limited by challenges such as varying image back...
关键词：GLAUCOMA fundus images machine learning nature-inspired algorithm SEGMENTATION classification 
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