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检索条件"主题词=Detection and tracking algorithms"

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High-precision laser centroid extraction algorithm for slight positional variations using four-quadrant detectors 14

High-precision laser centroid extraction algorithm for sligh...

引用

Optical Design and Testing XIV 2024

作者： Pan, Ning Zhao, Kaihang Li, Yuejia Liu, Huiwen Bai, Jian State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University Hangzhou310027 China College of Optical Science and Engineering Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou311215 China

ISBN: (纸本)9781510682023

This article presents a high-precision algorithm for extracting laser centroids using a four-quadrant detector (4QD), specifically designed for situations where laser position shifts happen on the nanoscale. The algorithm uses an iterative method to create a functional relationship between position changes and the differential output signals from the 4QD. We have validated the algorithm through simulations and experimental tests. © 2024 SPIE.

关键词： detection and tracking algorithms Sensors Signal detection Simulations Gaussian beams Photocurrent Nonlinear optics Optical simulations Photonics Position sensors

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Design and implementation of garbage classification and detection system based on YOLOv8 9

Design and implementation of garbage classification and dete...

引用

9th International Symposium on Sensors, Mechatronics, and Automation System, ISSMAS 2023

作者： Wang, Quanfu Wen, Bin Nanfang College Guangzhou 882 Wenquan Avenue Guangzhou China

ISBN: (纸本)9781510672802

Garbage classification can be seen everywhere in today's society, but due to the changes of the times, the awareness that different types of waste should go into different types of bins is not widespread among most people. Even some people don't even know what kinds of garbage there are. Therefore, it is very important to identify garbage. In order to speed up training and recognition, the author improved the YOLOv8 algorithm newly released this year, and at the same time used crawlers to crawl thousands of pictures of different types of garbage on the Internet for training. The author obtained the model with the highest accuracy by increasing the number of epochs and adjusting the batch. © 2024 SPIE.

关键词： Data modeling Education and training Object detection detection and tracking algorithms Classification systems Design and modelling Data conversion Convolution Image processing algorithms and systems Performance modeling

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detection of degradation indicator plants (wolfsbane) in grassland based on improved YOLOv5 algorithm 6

Detection of degradation indicator plants (wolfsbane) in gra...

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6th International Workshop on Advanced algorithms and Control Engineering, IWAACE 2022

作者： Li, Haiyang Ou, Weiyou Jin, Yunpeng Li, Kai Jiang, Jieteng Li, Chunmei Computer Technology and Application Department Qinghai University Qinghai Xining810016 China The Grassland Station of Qinghai Province Qinghai Xining810008 China

ISBN: (纸本)9781510657755

Studies by grassland workers have shown that the occurrence of degradation indicator plants in grassland is an important sign of grassland degradation. The detection of degradation indicator plants can provide a certain data basis for the study of grassland degradation. In this paper, a target detection algorithm for improving YOLOv5 model is proposed to detect the degradation indicator plants (wolfsbane) in grassland. Firstly, the target detection dataset of the grassland degradation indicator plant(wolfsbane)is constructed, and then the backbone network is optimized by adding a coordinate attention mechanism on the basis of the original YOLOv5 model;The original feature pyramid module in the feature fusion module is replaced by a weighted bidirectional feature pyramid (BiFPN) network structure, which realizes effective weighted feature fusion and bi-directional cross-scale connection;A small target detection layer is also added to further improve the detection accuracy of small targets. Experimental results show that the proposed improved algorithm achieves an average precision (AP) of 80.4%, which is 3.4% better than the original YOLOv5 model, and verifies the effectiveness of the improved model for the detection of degraded indicator plants (wolfsbane). © 2022 SPIE.

关键词： Target detection detection and tracking algorithms Image segmentation Data modeling Image enhancement Performance modeling Image processing algorithms and systems Lithium Neck Information fusion

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Fast 3D Object Segmentation Using DBSCAN Clustering Based on Supervoxel 2

Fast 3D Object Segmentation Using DBSCAN Clustering Based on...

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2nd International Conference on Signal Image Processing and Communication, ICSIPC 2022

作者： Yao, Tuo Yang, Qinghua Zhang, Rui School of Mechanical Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9781510657694

For visual perception of indoor mobile robots, real-time segmentation of 3D objects is a very challenging problem. Due to the complexity and disorder of indoor point cloud data, many methods have been proposed to improve the segmentation accuracy, which most of them cannot meet the requirement of rapidity. Therefore, this paper proposes a method for fast segmentation of 3D point clouds based on supervoxel density clustering. First, the ground under the indoor scene is removed by using plane fitting algorithm and the point cloud data after ground removal is denoised at the same time. Then, the target object is over-segmented to obtain the supervoxels with local geometric features. The core points of the nearest neighbors at the center of the supervoxels are searched out using the kdtree indexing acceleration. Finally, the density clustering of the supervoxels is performed based on the core point density up to. Experimental results on publicly available datasets show that our proposed method can effectively improve the speed of the algorithm while ensuring accuracy. © 2022 SPIE.

关键词： Clouds Image segmentation detection and tracking algorithms 3D acquisition 3D vision Data modeling Data processing Machine learning Visualization Voltage controlled current source

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Super resolving magnetic robotic system for wide coverage real time UXO detection

Super resolving magnetic robotic system for wide coverage re...

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detection and Remediation Technologies for Mines and Minelike Targets IV Conference

作者： Zalevsky, Z Bregman, Y Zafrir, H Tel Aviv Univ Fac Engn Dept Phys Elect IL-69978 Tel Aviv Israel

This paper introduces an advanced robotic system which combines both a sophisticated super resolving detection algorithm and a state of the art magnetic sensors used for a real time unexploded ordinance (UXO) detectio... 详细信息

ISBN: (纸本)0819431842

关键词： Magnetism Sensors detection and tracking algorithms Magnetic sensors Wavelets Target detection Signal to noise ratio Signal detection Robotic systems Magnetometers

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Improved wheat ear recognition method based on GAM-YOLOv8n 4

Improved wheat ear recognition method based on GAM-YOLOv8n

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4th International Conference on Advanced algorithms and Neural Networks, AANN 2024

作者： Song, Shiqiang Liu, Zuoshi Xu, Yaohui Jiangxi University of Science and Technology Jiangxi Ganzhou China

ISBN: (纸本)9781510686106

In view of the irregular shape of wheat ears, susceptibility to environmental light, and the dense and occluded state in the field, traditional methods of wheat ear recognition suffer from low accuracy, high error rates, and inefficiency. This paper proposes a GAM-YOLOv8n deep learning model for wheat ear detection. First, the GAM (Global Attention Module) is proposed to improve the capability of capturing features of wheat ears in the farmland. Next, the Wise IoU loss function is used to replace the original loss function of CIoU for a more precise measurement of the similarity between the real and predicted bounding boxes of the wheat ears. The improved show that compared with the initial YOLOv8n network, the improved network performance increases the Precison (P) by 3.7%, detection precision (PR) by 1.1%, and mean Average Precision (mAP) by 2.7%. © 2024 SPIE.

关键词： Ear Head Performance modeling detection and tracking algorithms Object detection Ablation Deep learning Target recognition Education and training Target detection

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Pattern recognition in the database of a mask layout

Pattern recognition in the database of a mask layout

引用

Conference on Photomask and Next-Generation Lithography Mask Technology IX

作者： Chen, SY Lynn, EC Shin, JJ Mentor Graphics Taiwan Ltd. (Taiwan) Taiwan Semiconductor Manufacturing Co. Ltd. (Taiwan)

ISBN: (纸本)0819445177

The request of pattern recognition has been frequently brought up by both mask and wafer engineers. Despite of different intentions, pattern recognition is usually the first step of many applications and hence plays a major role to accomplish certain tasks. For the purpose of this work, pattern recognition is defined as searching a specific polygon or a group of particular patterns from a chip layout. Operator scan is truly not an efficient approach of pattern recognition, in particular, for cases with huge design database of advanced semiconductor integrated circuits. Obviously, an automation system of pattern recognition is necessary and benefits the data preparation process. Two categories of pattern recognition are discussed in the present study, "fuzzy search" and "exact match." Each category has its own application, but the searching algorithms could be much different. Details of searching algorithms are given for both categories of pattern recognition. Due to the nature of industrial standard, the scope of the present application is limited to database with GDSII format. Hence, coordinate searching is internally used inside the searching engine.

关键词： Pattern recognition Genetic algorithms Fuzzy logic detection and tracking algorithms Optical proximity correction Databases Photomasks Semiconducting wafers Algorithm development Visualization

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Computer-aided detection of lung cancer on chest radiographs: Algorithm performance vs. radiologists' performance by size of cancer

Computer-aided detection of lung cancer on chest radiographs...

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Medical Imaging 2001 Conference

作者： Freedman, M Lo, SCB Lure, F Xu, XW Lin, J Zhao, H Osicka, T Zhang, R Georgetown Univ Med Ctr Washington DC 20007 USA

Our goal was to perform a pre-clinical test of the performance of a new pre-commercial system for detection of primary early-stage lung cancer on chest radiographs developed by Deus Technologies, LLC. The RapidScreen ... 详细信息

ISBN: (纸本)0819440051

关键词： Cancer Computer aided diagnosis and therapy Lung cancer Chest imaging Computing systems Remote sensing detection and tracking algorithms CAD systems System integration

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Research on Visual Recognition Method of Distribution Network Grounding Ring

Research on Visual Recognition Method of Distribution Networ...

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2023 International Conference on Computer Network Security and Software Engineering, CNSSE 2023

作者： Zhang, Qiuyan Xiao, Shuzhou Huang, Ruyun Zhang, Ruifeng Zeng, Peng Electric Power Research Institute of Guizhou Power Grid Co. Ltd. No. 32 Jiefang Road Nanming District Guizhou Province Guiyang City China

ISBN: (数字)9781510666528

ISBN: (纸本)9781510666511

The accurate identification of the grounding ring of the distribution network is the prerequisite for the grounding protection of the live working robot. In order to improve the recognition accuracy, this study improves the YOLOX network. In order to facilitate deployment on the host computer, this method is based on YOLOX-S, replaces the PAFPN feature utilization layer of the neck with a simplified BiFPN network, uses GIoU_Loss as the positioning loss function, and uses Focal Loss as the confidence prediction loss function. Experiments on the grounding ring of the distribution network verify the feasibility of the proposed identification method and meet the working requirements of live working robots. © 2023 SPIE.

关键词： detection and tracking algorithms Education and training Target detection Head Visualization Feature extraction Performance modeling Image fusion Feature fusion Neck

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An improved leader follower formation control algorithm 10

An improved leader follower formation control algorithm

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10th International Conference on Mechanical Engineering, Materials, and Automation Technology, MMEAT 2024

作者： Wang, Gang Ding, Simin School of Mechanical Engineering Jilin Communications Polytechnic Changchun130015 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China

ISBN: (纸本)9781510682634

In response to the problem that the leader's dominant role in the leader follower formation control algorithm can easily lead to the failure of formation system control, in this paper, the artificial potential field method is used to improve the virtual leader formation algorithm to solve the formation problem. The concept of virtual navigators is used for formation control, while the artificial potential field method is used for obstacle avoidance tasks. The combination of the two effectively solves the problem of traditional formation control being prone to failure. Through comparative simulation, it is found that under the use of the improved algorithm in this paper, the formation motion trajectory is more stable, and the time for the relative position error of formation members to stabilize is shortened by 15 seconds, indicating that the formation control under the algorithm in this paper is more stable and efficient. © 2024 SPIE.

关键词： Control systems Evolutionary algorithms Computer simulations Design Telecommunications detection and tracking algorithms Error analysis Navigation systems Windows Reflection

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