A Vision Method for Detecting Citrus Separation Lines Using Line-Structured Light [0.03%]
一种基于线结构光的柑橘分离线检测视觉方法
Qingcang Yu,Song Xue,Yang Zheng
Qingcang Yu
The detection of citrus separation lines is a crucial step in the citrus processing industry. Inspired by the achievements of line-structured light technology in surface defect detection, this paper proposes a method for detecting citrus se...
Enhancing YOLOv5 for Autonomous Driving: Efficient Attention-Based Object Detection on Edge Devices [0.03%]
基于注意力的边缘设备自主驾驶高效目标检测方法-YOLOv5改进版
Mortda A A Adam,Jules R Tapamo
Mortda A A Adam
On-road vision-based systems rely on object detection to ensure vehicle safety and efficiency, making it an essential component of autonomous driving. Deep learning methods show high performance; however, they often require special hardware...
SABE-YOLO: Structure-Aware and Boundary-Enhanced YOLO for Weld Seam Instance Segmentation [0.03%]
基于结构感知与边界增强的焊缝实例分割网络
Rui Wen,Wu Xie,Yong Fan et al.
Rui Wen et al.
Accurate weld seam recognition is essential in automated welding systems, as it directly affects path planning and welding quality. With the rapid advancement of industrial vision, weld seam instance segmentation has emerged as a prominent ...
Quantitative Magnetic Resonance Imaging and Patient-Reported Outcomes in Patients Undergoing Hip Labral Repair or Reconstruction [0.03%]
磁共振定量影像学和患者术后主观感受在髋关节盂唇修复或重建手术中的应用研究
Kyle S J Jamar,Adam Peszek,Catherine C Alder et al.
Kyle S J Jamar et al.
This study evaluates the relationship between preoperative cartilage quality, measured by T2 mapping, and patient-reported outcomes following labral tear treatment. We retrospectively reviewed patients aged 14-50 who underwent primary hip a...
Evaluating the Impact of 2D MRI Slice Orientation and Location on Alzheimer's Disease Diagnosis Using a Lightweight Convolutional Neural Network [0.03%]
基于轻量级卷积神经网络的阿尔茨海默病诊断中二维MRI切片方位和位置的影响评估
Nadia A Mohsin,Mohammed H Abdulameer
Nadia A Mohsin
Accurate detection of Alzheimer's disease (AD) is critical yet challenging for early medical intervention. Deep learning methods, especially convolutional neural networks (CNNs), have shown promising potential for improving diagnostic accur...
Road Marking Damage Degree Detection Based on Boundary Features Enhanced and Asymmetric Large Field-of-View Contextual Features [0.03%]
基于边界特征增强和不对称大视野上下文特征的路面标记损坏程度检测方法
Zheng Wang,Ryojun Ikeura,Soichiro Hayakawa et al.
Zheng Wang et al.
Road markings, as critical components of transportation infrastructure, are crucial for ensuring traffic safety. Accurate quantification of their damage severity is vital for effective maintenance prioritization. However, existing methods a...
Adaptive RGB-D Semantic Segmentation with Skip-Connection Fusion for Indoor Staircase and Elevator Localization [0.03%]
基于跳跃连接融合的室内楼梯和电梯定位自适应RGB-D语义分割方法
Zihan Zhu,Henghong Lin,Anastasia Ioannou et al.
Zihan Zhu et al.
Accurate semantic segmentation of indoor architectural elements, such as staircases and elevators, is critical for safe and efficient robotic navigation, particularly in complex multi-floor environments. Traditional fusion methods struggle ...
A Novel Method for Analysing the Curvature of the Anterior Lens: Multi-Radial Scheimpflug Imaging and Custom Conic Fitting Algorithm [0.03%]
一种分析前房曲率的新方法：多径向斯海姆普夫成像和自定义圆锥拟合算法
María Arcas-Carbonell,Elvira Orduna-Hospital,María Mechó-García et al.
María Arcas-Carbonell et al.
This study describes and validates a novel method for assessing anterior crystalline lens curvature along vertical and horizontal meridians using radial measurements derived from Scheimpflug imaging. The aim was to evaluate whether pupil di...
Advancing Early Blight Detection in Potato Leaves Through ZeroShot Learning [0.03%]
通过零样本学习推进土豆叶子早期病害检测
Muhammad Shoaib Farooq,Ayesha Kamran,Syed Atir Raza et al.
Muhammad Shoaib Farooq et al.
Potatoes are one of the world's most widely cultivated crops, but their yield is coming under mounting pressure from early blight, a fungal disease caused by Alternaria solani. Early detection and accurate identification are key to effectiv...
An Automated Method for Identifying Voids and Severe Loosening in GPR Images [0.03%]
一种在GPR图像中识别空洞和严重松动的自动化方法
Ze Chai,Zicheng Wang,Zeshan Xu et al.
Ze Chai et al.
This paper proposes a novel automatic recognition method for distinguishing voids and severe loosening in road structures based on features of ground-penetrating radar (GPR) B-scan images. By analyzing differences in image texture, the inte...