MSConv-YOLO: An Improved Small Target Detection Algorithm Based on YOLOv8 [0.03%]
基于YOLOv8的改进型小目标检测算法MSConv-YOLO
Linli Yang,Barmak Honarvar Shakibaei Asli
Linli Yang
Small object detection in UAV aerial imagery presents significant challenges due to scale variations, sparse feature representation, and complex backgrounds. To address these issues, this paper focuses on practical engineering improvements ...
Dynamic-Attentive Pooling Networks: A Hybrid Lightweight Deep Model for Lung Cancer Classification [0.03%]
动态注意池化网络：一种用于肺癌分类的轻量级深度学习模型
Williams Ayivi,Xiaoling Zhang,Wisdom Xornam Ativi et al.
Williams Ayivi et al.
Lung cancer is one of the leading causes of cancer-related mortality worldwide. The diagnosis of this disease remains a challenge due to the subtle and ambiguous nature of early-stage symptoms and imaging findings. Deep learning approaches,...
From Detection to Diagnosis: An Advanced Transfer Learning Pipeline Using YOLO11 with Morphological Post-Processing for Brain Tumor Analysis for MRI Images [0.03%]
从检测到诊断：使用YOLO11和形态学后处理的高级迁移学习管道，用于MRI图像脑肿瘤分析
Ikram Chourib
Ikram Chourib
Accurate and timely detection of brain tumors from magnetic resonance imaging (MRI) scans is critical for improving patient outcomes and informing therapeutic decision-making. However, the complex heterogeneity of tumor morphology, scarcity...
Deep Spectrogram Learning for Gunshot Classification: A Comparative Study of CNN Architectures and Time-Frequency Representations [0.03%]
基于深度频谱学习的枪声分类：几种CNN结构和时频表示方法的比较研究
Pafan Doungpaisan,Peerapol Khunarsa
Pafan Doungpaisan
Gunshot sound classification plays a crucial role in public safety, forensic investigations, and intelligent surveillance systems. This study evaluates the performance of deep learning models in classifying firearm sounds by analyzing twelv...
The Genetics of Amyloid Deposition: A Systematic Review of Genome-Wide Association Studies Using Amyloid PET Imaging in Alzheimer's Disease [0.03%]
淀粉样蛋白沉积的遗传学：使用阿尔茨海默病中淀粉样PET影像的全基因组关联研究系统性回顾
Amir A Amanullah,Melika Mirbod,Aarti Pandey et al.
Amir A Amanullah et al.
Positron emission tomography (PET) has become a powerful tool in Alzheimer's disease (AD) research by enabling in vivo visualization of pathological biomarkers. Recent efforts have aimed to integrate PET-derived imaging phenotypes with geno...
Fundus Image-Based Eye Disease Detection Using EfficientNetB3 Architecture [0.03%]
基于EfficientNetB3架构的视网膜眼病检测方法
Rahaf Alsohemi,Samia Dardouri
Rahaf Alsohemi
Accurate and early classification of retinal diseases such as diabetic retinopathy, cataract, and glaucoma is essential for preventing vision loss and improving clinical outcomes. Manual diagnosis from fundus images is often time-consuming ...
ODDM: Integration of SMOTE Tomek with Deep Learning on Imbalanced Color Fundus Images for Classification of Several Ocular Diseases [0.03%]
基于深度学习的不平衡彩色眼底图像若干眼科疾病分类方法研究
Afraz Danish Ali Qureshi,Hassaan Malik,Ahmad Naeem et al.
Afraz Danish Ali Qureshi et al.
Ocular disease (OD) represents a complex medical condition affecting humans. OD diagnosis is a challenging process in the current medical system, and blindness may occur if the disease is not detected at its initial phase. Recent studies sh...
Automated Task-Transfer Function Measurement for CT Image Quality Assessment Based on AAPM TG 233 [0.03%]
基于AAPM TG 233的CT图像质量评估的自动化任务传输功能测量方法
Choirul Anam,Riska Amilia,Ariij Naufal et al.
Choirul Anam et al.
This study aims to develop and validate software for the automatic measurement of the task-transfer function (TTF) based on the American Association of Physicists in Medicine (AAPM) Task Group (TG) 233. The software consists of two main sta...
The Contribution of AIDA (Artificial Intelligence Dystocia Algorithm) to Cesarean Section Within Robson Classification Group [0.03%]
AIDA在罗宾森分类分组中对剖宫产的贡献
Antonio Malvasi,Lorenzo E Malgieri,Michael Stark et al.
Antonio Malvasi et al.
Global cesarean section (CS) rates continue to rise, with the Robson classification widely used for analysis. However, Robson Group 2A patients (nulliparous women with induced labor) show disproportionately high CS rates that cannot be full...
A Lightweight CNN for Multiclass Retinal Disease Screening with Explainable AI [0.03%]
具有可解释性的人工智能的轻量级CNN视网膜多类疾病的筛查模型
Arjun Kumar Bose Arnob,Muhammad Hasibur Rashid Chayon,Fahmid Al Farid et al.
Arjun Kumar Bose Arnob et al.
Timely, balanced, and transparent detection of retinal diseases is essential to avert irreversible vision loss; however, current deep learning screeners are hampered by class imbalance, large models, and opaque reasoning. This paper present...