Collaborative Optimization of High-Resolution Representation and Miss-Sensitive Supervision for Aero-Engine Micro-Crack Detection [0.03%]
基于协作优化的涡轮发动机微裂纹缺陷检测方法研究
Zixuan Li,Jiaxin Liu,Hongwei Wang et al.
Zixuan Li et al.
Aero-engine blades operate under extreme conditions involving high temperature, pressure, rotational speed, and cyclic loads, making them susceptible to surface defects such as micro-cracks. Due to their small scale, weak edges, low contras...
Weighted Sampling with Frequency-Aware Spatial Attention for Imbalanced Image Classification [0.03%]
基于频率感知空间注意力的加权采样方法对抗不平衡图像分类问题
Shiqi Zhang,Peng Li
Shiqi Zhang
Class imbalance remains a critical challenge in image classification, where underrepresented classes often receive insufficient training attention and exhibit poor recognition performance. In this study, we propose a hybrid framework that c...
Research on Integrated Technologies for Space Target Imaging, Ranging, and Communication [0.03%]
空间目标一体化探测识别技术研究
Xiansong Gu,Qiang Fu,Zhuang Liu et al.
Xiansong Gu et al.
The integration requirements of laser ranging, imaging, and communication functions in space target detection have placed higher demands on system performance. This paper takes a modularly designed integrated laser ranging, imaging, and com...
Abnormal Discrepancy-Guided Knowledge Distillation for Image Anomaly Detection [0.03%]
用于图像异常检测的异常差异引导知识蒸馏方法
Zhenjun Yu,Lin Sun,Kai Wang et al.
Zhenjun Yu et al.
Knowledge distillation is a cornerstone of image anomaly detection for amplifying subtle defects via teacher-student discrepancy, yet existing methods rely on feature alignment loss that causes reconstruction error confusion and degrades ac...
TransLiteUNet: A Lightweight CNN-Transformer Hybrid for Efficient 3D Brain Tumor Segmentation with Sub-0.5 M Parameters [0.03%]
基于轻量级CNN-变压器混合模型的高效脑肿瘤分割方法（参数量小于0.5M）
Lixin Zhou,Yuanyuan Yang,Yunfeng Yang
Lixin Zhou
Transformer, with its unique self-attention mechanism, naturally excels in modeling global features. Convolutional Neural Networks (CNNs), on the other hand, leverage strong spatial inductive biases to effectively capture local features wit...
Reliable Pseudo-Labeling and Confusion Calibration for Foggy-Scene Semantic Segmentation [0.03%]
可靠的伪标签和混淆校准用于雾景语义分割
Shuai Yan,Shirong Feng,Zhicheng Wei
Shuai Yan
Semantic segmentation in foggy scenes is crucial for autonomous driving systems, yet acquiring annotated real-world foggy data is highly costly. Existing unsupervised domain adaptation methods typically adopt a self-training strategy, adapt...
GDNet: A Robust 2.5D Multimodal MRI Brain Tumor Segmentation Framework with EMA Stabilization and Tumor-Aware Sampling [0.03%]
具有EMA稳定和肿瘤感知采样的稳健的2.5d多模态MRI脑肿瘤分割框架
Behnam Kiani Kalejahi,Sajid Khan,Mohammad Javad Rajabi
Behnam Kiani Kalejahi
Accurate, automated delineation of adult diffuse gliomas from multi-parametric magnetic resonance imaging (mpMRI) is central to quantitative neuro-oncology. Volumetric 3D networks dominate the BraTS leaderboard but require expensive GPUs, l...
Radiomics in Lung Cancer Imaging: A Narrative Review of Current Evidence [0.03%]
放射组学在肺癌影像中的应用：现有证据的回顾性研究
Andrea Lastrucci,Nicola Iosca,Edoardo Cavigli et al.
Andrea Lastrucci et al.
Background: Lung cancer remains the leading cause of cancer-related mortality worldwide, and early diagnosis and accurate disease stratification are still major clinical challenges. Radiomics has emerged as a quantitative...
An Unsupervised Deep Learning Framework for Quantitative Breast Density Estimation from Mammograms [0.03%]
一种无监督深度学习框架用于从乳房X线照片中进行定量的乳腺密度估计
Khaldoon Alhusari,Salam Dhou
Khaldoon Alhusari
Breast cancer is the most commonly diagnosed cancer in women, with early detection playing a critical role in clinical outcomes. Mammography remains the standard screening modality, producing X-ray images used to assess mammographic density...
AI-Based Detection of Osteoporosis on Dental Radiographs: Influence of Region-of-Interest Selection on Classification Performance [0.03%]
基于人工智能的牙科放射影像骨质疏松检测：感兴趣区域选择对分类性能的影响
Michael Moncher,Vincent Traboulsi,Florian Kofler et al.
Michael Moncher et al.
Osteoporosis may alter mandibular bone structure and peri-implant remodeling, but it remains unclear whether such changes are detectable on dental radiographs using deep learning. This retrospective study evaluated whether osteoporosis can ...