Computers in Industry最新文献_第3页

Measure2Shape: A novel footwear customisation framework utilising 3D shape estimation from anthropometric measurements with an orthosis case study

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-05 DOI: 10.1016/j.compind.2025.104257

Zhaohua Zhu , Wenxuan Ji , Yadie Yang , Sio-Kei Im , Jie Zhang

{"title":"Measure2Shape: A novel footwear customisation framework utilising 3D shape estimation from anthropometric measurements with an orthosis case study","authors":"Zhaohua Zhu , Wenxuan Ji , Yadie Yang , Sio-Kei Im , Jie Zhang","doi":"10.1016/j.compind.2025.104257","DOIUrl":"10.1016/j.compind.2025.104257","url":null,"abstract":"<div><div>To address the limitations of relying on expensive 3D scanners for obtaining foot data in footwear customisation, this paper introduces a novel framework, Measure2Shape, which estimates 3D foot shapes using anthropometric measurement data. To achieve this, we established a large-scale 3D foot dataset with measurement data and created statistical shape models (SSMs) to represent the range of foot variations. We then proposed efficient forward- and backward-search algorithms to accurately determine the regression matrix, which connects the optimal combination of 3D measurements to the SSM coefficients of the 3D foot shape. Compared to existing 3D foot model estimation methods, our approach achieves high-precision 3D foot shape predictions using fewer dimensional measurements, with the optimal number being 6 and an average prediction error of 2.49 (±0.75) mm. Additionally, orthosis designed based on the predicted 3D foot model effectively reduce both static and dynamic peak plantar pressures, validating the reliability of our model. More importantly, the proposed regression search method can be extended to 3D estimations for other body regions, offering a wide range of customisation solutions beyond footwear. In the future, we will further expand the dataset to build a more robust 3D foot prediction model. Our project will be publicly available at: <span><span>https://github.com/Easy-Shu/Measure2Shape</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"167 ","pages":"Article 104257"},"PeriodicalIF":8.2,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143125022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An immersive spatially consistent multi-modal augmented virtuality human-machine interface for telerobotic systems

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-05 DOI: 10.1016/j.compind.2025.104260

Rebecca Schwenk, Shana Smith

{"title":"An immersive spatially consistent multi-modal augmented virtuality human-machine interface for telerobotic systems","authors":"Rebecca Schwenk, Shana Smith","doi":"10.1016/j.compind.2025.104260","DOIUrl":"10.1016/j.compind.2025.104260","url":null,"abstract":"<div><div>This study presents an immersive augmented virtuality (AV)-based human-machine interface (HMI) designed to enhance telepresence and operator performance in telerobotic systems. Traditional telerobotic systems often face limitations such as 2D representations of 3D environments, restricted fields of view, and reduced depth perception, all of which hinder operator effectiveness. Although extended reality and various augmentation technologies have been employed to create more intuitive teleoperations, prior research has largely overlooked the integration of spatially consistent video streams from remote sites, which significantly increases operators' mental workload. As a result, these systems struggled to manage dynamic changes at the remote site and lacked sufficient environmental context and an unlimited field of view for operators. This study addresses these limitations by augmenting the virtual replica of the remote environment with a real-time, spatially consistent video stream within the AV-based HMI, enabling operators to better understand dynamic changes at the remote site and enhancing both situational awareness and control precision during teleoperations. Additionally, 3D point clouds and haptic feedback are integrated to create a multi-modal interface that further improves operator perception and interaction with the remote environment. A user study comparing the immersive AV-based HMI with a multi-monocular HMI demonstrated significant improvements in task workload, system usability, spatial presence, and task completion times. Participant feedback further confirmed the system’s ability to improve operator performance.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"167 ","pages":"Article 104260"},"PeriodicalIF":8.2,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143125282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating unsignalized crosswalk safety in the age of autonomous vehicles

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-03 DOI: 10.1016/j.compind.2025.104259

Andrea Avignone , Marco Bassani , Beatrice Borgogno , Brunella Caroleo , Silvia Chiusano , Federico Princiotto

{"title":"Evaluating unsignalized crosswalk safety in the age of autonomous vehicles","authors":"Andrea Avignone , Marco Bassani , Beatrice Borgogno , Brunella Caroleo , Silvia Chiusano , Federico Princiotto","doi":"10.1016/j.compind.2025.104259","DOIUrl":"10.1016/j.compind.2025.104259","url":null,"abstract":"<div><div>As autonomous vehicles are poised to enter public roadways, a major concern is their interaction with pedestrians. It requires attention and ability for pedestrians to interact correctly and for autonomous vehicles to detect pedestrians hence avoiding collisions. We propose a complete pipeline to collect, process and elaborate video data to quantitatively assess the possible occurrence of conflicts. It integrates computer vision techniques and a conflict detection system to evaluate these interactions by rigorously implementing the theoretical formulation of two primary metrics: Time-to-Collision (TTC) for the pre-event phase and Post Encroachment Time (PET) for the post-event phase. This study is conducted in a real-world setting with mixed traffic conditions to analyse the differences in pedestrian interactions with both human-operated and autonomous vehicles during daytime. The computation of conflict measures allowed us to identify possible conflicts and assess the safety at an unsignalized crossing, in which pedestrians are exposed to more risky conflicts. The results obtained show a higher incidence of more severe conflicts for interactions between pedestrians and human-operated vehicles, which highlights the caution taken in programming the autonomous vehicle.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"167 ","pages":"Article 104259"},"PeriodicalIF":8.2,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143125024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent prediction and soft-sensing of comprehensive production indicators for iron ore sintering: A review 铁矿石烧结综合生产指标的智能预测与软测量研究进展

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-01 DOI: 10.1016/j.compind.2024.104215

Sheng Du , Xian Ma , Haipeng Fan , Jie Hu , Weihua Cao , Min Wu , Witold Pedrycz

{"title":"Intelligent prediction and soft-sensing of comprehensive production indicators for iron ore sintering: A review","authors":"Sheng Du , Xian Ma , Haipeng Fan , Jie Hu , Weihua Cao , Min Wu , Witold Pedrycz","doi":"10.1016/j.compind.2024.104215","DOIUrl":"10.1016/j.compind.2024.104215","url":null,"abstract":"<div><div>Iron ore sintering is a critical process in iron and steel production, with a substantial impact on overall energy consumption and the emission of various environmental pollutants. Enhancing the efficiency of this process is crucial for achieving sustainability in the iron and steel industry. Accurate prediction and real-time monitoring of comprehensive production indicators are essential for optimizing production and improving energy efficiency. This paper provides a systematic review of intelligent prediction and soft-sensing techniques applied to the iron ore sintering process. It details the mechanisms and operational principles of these technologies, with a focus on key indicators such as quality, thermal state, yield, and energy consumption. This paper explores the current state-of-the-art in four prediction methodologies: mechanism analysis-based methods, data feature analysis-based methods, multi-model fusion-based methods, and operating mode recognition-based methods. Finally, the challenges to the current comprehensive production indicator prediction of the sintering process are pointed out, including the difficulty of dealing with the changing operating mode, the incomplete analysis of image features, and the insufficient consideration of the differences in data distribution. In the future, operating mode recognition approaches, deep learning approaches, transfer learning approaches, and computer vision techniques will have a broad prospect in the comprehensive production indicator prediction of the sintering process.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"165 ","pages":"Article 104215"},"PeriodicalIF":8.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142804460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Meta-task interpolation-based data augmentation for imbalanced health status recognition of complex equipment 基于元任务插值的复杂设备不平衡健康状态识别数据增强

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-01 DOI: 10.1016/j.compind.2024.104226

Jinyuan Li, Wenqing Wan, Yong Feng, Jinglong Chen

{"title":"Meta-task interpolation-based data augmentation for imbalanced health status recognition of complex equipment","authors":"Jinyuan Li, Wenqing Wan, Yong Feng, Jinglong Chen","doi":"10.1016/j.compind.2024.104226","DOIUrl":"10.1016/j.compind.2024.104226","url":null,"abstract":"<div><div>In the research of health status detection technology for complex equipment such as liquid rocket engines, the extreme working environment hinders the widespread conduct of fault experimental simulations, leading to data scarcity and imbalance. Consequently, the performance of intelligent models deteriorates rapidly with direct training. To address this issue, this paper proposes a meta-task feature space interpolation network model. Firstly, the model uses an encoder to map randomly selected task pairs to a more discriminative feature space, and then interpolates corresponding features and labels within this latent feature space to generate additional tasks, increasing the distribution density of tasks and alleviating the problem of insufficient training tasks. Furthermore, the model leverages self-distillation to improve the learning of label information. By integrating soft labels with supervised labels, it captures the hidden category information of newly interpolated tasks, thereby reducing the impact of class imbalance on model performance. The effectiveness of the proposed method is validated through a series of experiments conducted across three different scenarios. The results demonstrate that the proposed method achieves an average accuracy of 97.91% on the turbopump bearing dataset, which is a significant improvement over the comparative methods.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"165 ","pages":"Article 104226"},"PeriodicalIF":8.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integration of industry 4.0 technologies for agri-food supply chain resilience 整合工业4.0技术提升农业食品供应链弹性

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-01 DOI: 10.1016/j.compind.2024.104225

Rohit Sharma , Balan Sundarakani , Ioannis Manikas

{"title":"Integration of industry 4.0 technologies for agri-food supply chain resilience","authors":"Rohit Sharma , Balan Sundarakani , Ioannis Manikas","doi":"10.1016/j.compind.2024.104225","DOIUrl":"10.1016/j.compind.2024.104225","url":null,"abstract":"<div><div>The agri-food supply chain (AFSC) operations are becoming challenging due to globalization, constantly shifting consumer demands, and intensive disruptions leading to inefficient production and distribution of safe and high-quality food. Technological advancements are the most promising ways to ensure firms’ survival and supply chains. To enhance the resilience of AFSCs, the present study aims to identify and model the challenges associated with AFSC operations in the context of the United Arab Emirates (UAE) food processing industry. An integrated methodology using the Grey Influence Analysis (GINA) and Fuzzy Linguistic Quantifier Ordered Weighted Aggregation (FLQOWA) methodology is applied to analyze resilience enablers and assess industry 4.0 technologies (I4Ts) that can enhance resilience in AFSCs. The GINA technique helps identify the most influential resilience enablers, and the FLQOWA helps assess and prioritize I4Ts to enhance resilient enablers. The findings reveal that out of thirteen sub-enablers, four are the most influential resilient enablers, viz., real-time information sharing, enhanced product traceability, improved risk management, and planning and network design; and out of ten I4Ts, three are the most influential technologies viz., big data analytics, Internet of things, and cloud computing can further enhance resilience enablers. The findings from the study can help AFSC organizations and the government formulate appropriate strategies based on the integrated matrix developed by selecting the best combination of technologies for strengthening the required resilient enablers among the AFSC stakeholders.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"165 ","pages":"Article 104225"},"PeriodicalIF":8.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BlurRes-UNet: A novel neural network for automated surface characterisation in metrology BlurRes-UNet：一种新的神经网络，用于计量中的自动表面表征

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-01 DOI: 10.1016/j.compind.2024.104228

Weixin Cui , Shan Lou , Wenhan Zeng , Visakan Kadirkamanathan , Yuchu Qin , Paul J. Scott , Xiangqian Jiang

{"title":"BlurRes-UNet: A novel neural network for automated surface characterisation in metrology","authors":"Weixin Cui , Shan Lou , Wenhan Zeng , Visakan Kadirkamanathan , Yuchu Qin , Paul J. Scott , Xiangqian Jiang","doi":"10.1016/j.compind.2024.104228","DOIUrl":"10.1016/j.compind.2024.104228","url":null,"abstract":"<div><div>Surface characterisation is essential in metrology for precise measurement and analysis of surface features, ensuring product quality and compliance with industry standards. Form removal is the primary step in surface characterisation, isolating features of interest by eliminating the primary shape from measurements. Traditional least-squares methods, as specified in ISO standards, are effective but offer limited adaptability for diverse surfaces and often require manual parameter tuning. With this limitation in mind, this paper proposes BlurRes-UNet, a deep learning-based model designed for fully automatic form removal. Built on an encoder–decoder architecture with residual learning, skip connections, and a tailored loss function, the model incorporates domain knowledge, feature engineering, and regularisation techniques to optimise performance with limited training data. The model is evaluated against traditional least squares methods and assessed using various strategies to demonstrate its performance and robustness. It processes surfaces of 256 × 256 resolution in 7.32 ms per sample on a T4 GPU, achieving superior accuracy in recognising reference forms across diverse surfaces compared to traditional methods. The results suggest that the model is capable of accurately recognising different order reference forms from diverse surfaces, facilitating an autonomous surface characterisation system without the need for manual intervention.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"165 ","pages":"Article 104228"},"PeriodicalIF":8.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142911787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A robotic skill transfer learning framework of dynamic manipulation for fabric placement 织物放置动态操作的机器人技能迁移学习框架

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-01 DOI: 10.1016/j.compind.2024.104216

Tianyu Fu , Cheng Li , Yunfeng Bai , Fengming Li , Jiang Wu , Chaoqun Wang , Rui Song

{"title":"A robotic skill transfer learning framework of dynamic manipulation for fabric placement","authors":"Tianyu Fu , Cheng Li , Yunfeng Bai , Fengming Li , Jiang Wu , Chaoqun Wang , Rui Song","doi":"10.1016/j.compind.2024.104216","DOIUrl":"10.1016/j.compind.2024.104216","url":null,"abstract":"<div><div>Placing fabric poses a challenge to robots since fabric with high dimensional configuration space can deform during manipulation. Existing methods for placing fabric mostly rely on static operations, which are inefficient and require a large workspace. Therefore, this study applies dynamic manipulation (manipulating uncontrollable parts of the fabric by swinging) to fabric placement, proposing a novel learning framework for robotic dynamic fabric placement skill learning and generalization. The proposed framework integrates reinforcement learning with imitation learning, leveraging expert demonstration data to guide and accelerate skill acquisition. Additionally, fabric characteristics are combined with imitation learning to enable the transfer and generalization of the learned policy to real-world environments The experiments suggest that the proposed framework is capable of achieving the placement tasks for a range of positions and fabrics. For success rate, the policy of the proposed framework ultimately achieves a flatness of exceeding 95% and a placement distance error of less than 2 mm. Moreover, the proposed approach is similar in operation time to the fastest method, while it can reduce the space required for manipulating the fabric by over 15%. Compared with other placement policies, it is promising because of its high accuracy, flexibility, efficiency, as well as adaptability.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"165 ","pages":"Article 104216"},"PeriodicalIF":8.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142763009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A context-aware decision support system for selecting explainable artificial intelligence methods in business organizations 在商业组织中选择可解释的人工智能方法的上下文感知决策支持系统

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-01 DOI: 10.1016/j.compind.2024.104233

Marcelo I. Reis , João N.C. Gonçalves , Paulo Cortez , M. Sameiro Carvalho , João M. Fernandes

{"title":"A context-aware decision support system for selecting explainable artificial intelligence methods in business organizations","authors":"Marcelo I. Reis , João N.C. Gonçalves , Paulo Cortez , M. Sameiro Carvalho , João M. Fernandes","doi":"10.1016/j.compind.2024.104233","DOIUrl":"10.1016/j.compind.2024.104233","url":null,"abstract":"<div><div>Explainable Artificial Intelligence (XAI) methods are valuable tools for promoting understanding, trust, and efficient use of Artificial Intelligence (AI) systems in business organizations. However, the question of how organizations should select suitable XAI methods for a given task and business context remains a challenge, particularly when the number of methods available in the literature continues to increase. Here, we propose a context-aware decision support system (DSS) to select, from a given set of XAI methods, those with higher suitability to the needs of stakeholders operating in a given AI-based business problem. By including the human-in-the-loop, our DSS comprises an application-grounded analytical metric designed to facilitate the selection of XAI methods that align with the business stakeholders’ desiderata and promote a deeper understanding of the results generated by a given machine learning model. The proposed system was tested on a real supply chain demand problem, using real data and real users. The results provide evidence on the usefulness of our metric in selecting XAI methods based on the feedback and analytical maturity of stakeholders from the deployment context. We believe that our DSS is sufficiently flexible and understandable to be applied in a variety of business contexts, with stakeholders with varying degrees of AI literacy.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"165 ","pages":"Article 104233"},"PeriodicalIF":8.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142911788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

YOLOv10-pose and YOLOv9-pose: Real-time strawberry stalk pose detection models YOLOv10-pose和YOLOv9-pose：实时草莓茎秆姿态检测模型

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2025-02-01 DOI: 10.1016/j.compind.2024.104231

Zhichao Meng , Xiaoqiang Du , Ranjan Sapkota , Zenghong Ma , Hongchao Cheng

{"title":"YOLOv10-pose and YOLOv9-pose: Real-time strawberry stalk pose detection models","authors":"Zhichao Meng , Xiaoqiang Du , Ranjan Sapkota , Zenghong Ma , Hongchao Cheng","doi":"10.1016/j.compind.2024.104231","DOIUrl":"10.1016/j.compind.2024.104231","url":null,"abstract":"<div><div>In the computer-aided industry, particularly within the domain of agricultural automation, fruit pose detection is critical for optimizing efficiency across various applications such as robotic harvesting, aerial crop surveillance, precision pruning, and automated sorting. These technologies enhance productivity and precision, addressing challenges posed by an aging labor force and the increasing demand for sophisticated robotic applications in agriculture. This is particularly crucial for strawberries, which are globally recognized for their high nutritional value. The strawberry pickting robots generally cut the stems, so knowing the pose of the strawberry stalks before cutting can effectively adjust the pose of the end effector, thereby improving the success rate of picking. This paper referred to the keypoint detection branch and loss function of the YOLOv8-pose model, and combined the latest YOLOv9 and YOLOv10 object detection models to propose YOLOv9-pose and YOLOv10-pose. The experimental results showed that YOLOv9-base-pose had the best comprehensive performance, reaching 0.962 in Box_mAP50 and 0.914 in Pose_mAP50, and the speed met the real-time requirement of FPS 51. The entire YOLOv10-pose series did not achieve satisfactory accuracy, but not using non-maximum suppression did indeed speed up the post-processing. In the YOLOv10-pose series, YOLOv10m-pose achieved the best comprehensive performance with Box_mAP50 of 0.954, Pose_ mAP50 of 0.903, and a speed of 61 FPS. Comparing YOLOv9-base-pose with the entire series of YOLOv8-pose and YOLOv5-pose also demonstrated the superior performance of YOLOv9-base-pose. YOLOv9-pose and YOLOv10-pose can provide a theoretical basis for pose detection and a reference for other similar fruit pose detection.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"165 ","pages":"Article 104231"},"PeriodicalIF":8.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0