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共 15862 条记录，以下是231-240 订阅

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Performance analysis of YOLO-DeepSORT on Thermal Video-Based Online Multi-object Tracking 3

Performance Analysis of YOLO-DeepSORT on Thermal Video-Based...

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3rd international conference on robotics, Automation and Artificial intelligence (RAAI)

作者： Ibrahim, Nur Darlis, Arsyad Ramadhan Herianto Kusumoputro, Benyamin Univ Indonesia Fac Engn Dept Elect Engn Res Ctr Artificial Intelligence & Data Engn Depok Indonesia Darma Persada Univ Fac Engn Informat Syst Study Program Jakarta Indonesia

ISBN: (纸本)9798350307573;9798350307566

Recently, thermal cameras have been used in various fields, including surveillance systems and advanced driver assistance systems (ADAS), as they perform better in low light than visible-light cameras. Some challenges in the surveillance system or ADAS field related to thermal cameras are occlusion and thermal crossover between objects with similar appearances during object detection or object tracking tasks, which can lead to misdetection, false positives, and lost tracking. In this paper, performance analysis of you-only-look-once (YOLO) combined with deep online real-time tracking (DeepSORT) on thermal video-based online multi-object tracking (MOT) in occlusion and thermal crossover scene is presented. YOLO, as one of state-ofthe-art method for detection task, is used for detection system. Then, the detected object from YOLO is tracked using DeepSORT. The results demonstrate that the online MOT of sequential thermal images using YOLO-DeepSORT achieved a MOTA score of 44.2% and IDF1 of 45.3%. Thus, negative example was added in YOLO training process to reduce false detection, and it gives improvement with MOTA score of 63.8% and IDF1 score of 54.6%.

关键词： YOLO DeepSORT online multi-object tracking thermal image negative example

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Brain tumor detection using texture based LBP feature on MRI images using feature selection technique

Brain tumor detection using texture based LBP feature on MRI...

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international conference on Artificial intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Guleria, Vishal Verma, Aryan Dhenkawat, Rishabh Chaurasia, Uttkarsh Singh, Nagendra Pratap Department of Computer Science and Engineering National Institute of Technology H.P. Hamirpur India

ISBN: (纸本)9781032669663

This study analyzes the utility of texture-based local binary pattern features to spot brain cancers. Local Binary pattern is a highly effective texture feature that uses a three-bythree sliding window to label the pixels of an image by thresholding the adjacent pixel. To prepossess images, they are first converted from RGB to Lab to narrow the color space, and then this image is operated with Principal component analysis. This processed image is used to extract the LBP features. Finally, Support vector machines are trained on the extracted features from the dataset and compared against the deep neural network results. We found that the deep neural network achieves 98.6% accuracy while the SVM approach achieves an accuracy of 98.4%. Finally, a comparison has been drawn between these approaches using various comparison metrics. © 2024 The Author(s).

关键词： Local binary pattern

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Evaluation of Emotional intelligence for Academic Stress analysis 8

Evaluation of Emotional Intelligence for Academic Stress Ana...

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8th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Khan, Asif Siddiqui, Mohammad Atif Integral University Integral Robotics Lab Department of Computer Application Lucknow India Integral University Integral Robotics Lab Department of Electrical Engineering Lucknow India

ISBN: (纸本)9798350376425

The research study on the "Design and Implementation of an AI-Enhanced Mental Health Tool for Academic Stress"addresses the growing mental health crisis among students, particularly concerning academic pressures. The study highlights alarming statistics, such as over 13,000 student suicides in India in 2021 - a 4.5% increase from the previous year and a 70% rise since 2011 - indicating an urgent need for targeted interventions. The academic environment, characterized by high expectations, intense pressure, and fierce competition, places considerable strain on students' mental well-being. Recognizing that one-size-fits-all solutions are inadequate, this research advocates for a personalized approach to address these unique challenges. Artificial intelligence (AI) is positioned as a key solution in this effort. The proposed AI-enhanced mental health tool aims to provide students with real-time, personalized support. Through proactive interventions and individualized assistance, it seeks to revolutionize mental health care in academic settings. This study underscores the importance of innovative approaches to tackling the student mental health crisis. By fostering resilience and well-being, the AI tool aims to effectively address academic stress and improve mental health outcomes. © 2024 IEEE.

关键词： Emotional intelligence

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5th international conference on Deep Learning, Artificial intelligence and robotics, ICDLAIR 2023

5th International Conference on Deep Learning, Artificial In...

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5th international conference on Deep Learning, Artificial intelligence and robotics, ICDLAIR 2023

ISBN: (纸本)9783031609343

The proceedings contain 70 papers. The special focus in this conference is on Deep Learning, Artificial intelligence and robotics. The topics include: A Short Survey on Comparative Study of Modern Cryptography Approach;advances in Computer-Aided Detection and Diagnosis of Retinal Diseases: A Comprehensive Survey of Fundal Image analysis;driver Safety and Drowsiness Detection in Internet of Vehicles with Federated Learning;privacy Preserving Fingerprint Classification Using Federated Learning;comparative Study of Ensemble Learning Models for Smart Meter Load;social-Media Video Summarization Using Convolutional Neural Network and Kohnen’s Self Organizing Map;machine Learning and Deep Leaning in Predicting Coronary Heart Disease;Augmented Super Resolution GAN (ASRGAN) for Image Enhancement Through Reinforced Discriminator;Convolutional Block Attention Assisted Dense Stacked Bi-LSTM for the Generation of RDF Statements;real-Time Permanent Change Proposals for Abandoned Object Detection;an Excursion to Ontology-Based Non-functional Requirements Specification;a Review of Traditional and Neural Network Methods for Protecting Privacy in Big Data Analytics;a Long Short-Term Memory Learning Based Malicious Node Detection for Clustering in Wireless Sensor Networks;experimental analysis for Sensor Reduction to Depict Real-Time Applications Through Regression Techniques;multi-resolution Neural Network for Road Scene Segmentation;A CNN-Based Road Accident Detection and Comparison of Classification Techniques;football Match Result Prediction Using Twitter Statistical/Historical Data;safeguarding Ecosystems and Efficiency in Peer-to-Peer File Sharing Systems: An IoT-Inspired Approach to Pollution Mitigation;a Heuristic for Minimizing Resource Requirement for Quantum Graph Neural Networks;Light-Gated Recurrent Unit Based Acoustic Modeling for Improved Hindi ASR;Detecting Phishing URLs Using Machine Learning: A Review;comparative analysis of Pneumonia Detection from Chest X-ray Using

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A study on Employee Perception of Artificial intelligence in the Recruitment process of an IT Organization

A study on Employee Perception of Artificial Intelligence in...

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2023 international conference on the Confluence of Advancements in robotics, Vision and Interdisciplinary Technology Management, IC-RVITM 2023

作者： Sethumadhavan, R. Dayananda Sagar College of Engineering Department of Mba Karnataka Bangalore India

ISBN: (纸本)9798350306088

A study is conducted on employees' perception of artificial intelligence in an organization's hiring process. The objective of the research is to find out how employees perceive the importance of artificial intelligence in the recruiting process of an IT organization. The research design is descriptive in nature. Simple random sampling is used in the study and the sample size is 101. The data is collected using the questionnaire and the analysis is done using Chi- square, ANOVA and correlation. AI has been proven to provide a better candidate experience, reduce time to hire, and save time. Most employees agreed that procurement could be made faster by using AI. According to the study, the use of AI can also achieve unbiased applicant screening. AI helps the recruiters and is very important for better documentation, recruiting at scale, time and cost savings, automated interviews, etc. © 2023 IEEE.

关键词： Artificial intelligence

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Visual Data Restoration for Pipeline Inspection Robots by Compressed Sensing 8

Visual Data Restoration for Pipeline Inspection Robots by Co...

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8th international conference on robotics, Control and Automation (ICRCA)

作者： Zamora, Johnatan D. Tang, Chaoqing Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China

ISBN: (纸本)9798350344738;9798350344721

Pipelines are the key infrastructure for gas and liquid fossil energy, any leakage on the transportation pipelines lead to disasters for human safety and environment. The most popular method for the health monitoring of it is using pipeline inspection robots. The circumferential-deployed sensors capture two-dimensional data, i.e. visual images for defect analysis. However, due to the high vibration and harsh environment in pipelines, sensor failure becomes the common cases. Fixing this sensor failure is solving one visual data restoration problem, so this paper proposes one compressed sensing (CS)-based method. The core idea is that sampling a partial pixels in one image can full reconstruct the full image with CS theory, and the health sensor values are regarded as the CS sampling values. Block-byblock restoration scheme is used. The experimental results on real pipeline inspection data show our proposed CS method has better performance than the traditional interpolation method for most typical features, e.g. 20% of improvement on 2D coefficients with baseline for spiral weld, 53% of improvement on root-meansquare-error on defect region.

关键词： pipelines inspection visual images analysis compressed sensing

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Optimizing Robotic Automatic Suturing Through VR-Enhanced Data Generation for Reinforcement Learning Algorithms 6

Optimizing Robotic Automatic Suturing Through VR-Enhanced Da...

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6th IEEE international conference on Artificial intelligence and eXtended and Virtual Reality, AIxVR 2024

作者： Nieto, N. Sanchez, J.A. Aguirre, M.G. Felix, F. Munoz, L.A. Tec de Monterrey Engineering Sciences Dept. N.L. Monterrey Mexico

ISBN: (纸本)9798350372021

This paper explores the integration of Virtual Reality(VR) to a Surgical Robotic Simulation to enhance the quality of data used for training a ground-truth algorithm for surgical procedures performed by the DaVinci robot inside a simulated environment. As it is to be demonstrated by this paper, VR and Reinforcement Learning (RL) techniques can significantly improve the realism and effectiveness of the training data compared to traditional methods. It also investigates and deepens the study of incorporating Cognitive Vision theories to guide the learning process, following the premise that the full-immersion visual and haptic feedback models will result in better quality training data for the surgical robot to perform an autonomous surgery algorithm, leading to more accurate and adaptable minimally-invasive robotic surgery (MIRS) systems. This research was inspired and shaped by our active participation in the 2023-2024 AccelNet Surgical robotics Challenge. © 2024 IEEE.

关键词： Motion analysis

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To Be Human-like or Machine-like? An Empirical Research on User Trust in AI Applications in Service Industry 8

To Be Human-like or Machine-like? An Empirical Research on U...

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8th international conference on Automation, robotics and Applications (ICARA)

作者： Zhang, Aihua Yang, Qiqi Beijing Univ Posts & Telecommun Sch Econ & Management Beijing Peoples R China

ISBN: (纸本)9781665483834

This research investigates user trust in artificial intelligence (AI) applications based on empirical analysis of intelligent service robots in service industry. We examined the impacts of human-like design of AI robots on intelligence and anthropomorphism perceived by users. The relationships between perceived intelligence, perceived anthropomorphism, and level of trust were also tested. An online survey with a between-subject design was conducted to collect data. The results indicate that robots with physical human-like appearance were perceived lower level of anthropomorphism and intelligence, and interaction function design on robots does not significantly increase those perceptions. Moreover, the significant effect of perceived intelligence on perceived anthropomorphism was confirmed, and both perceptions of users exert positive effect on their trust in AI robots.

关键词： artificial intelligence anthropomorphism human-robot interaction trust human-like appearance interaction function

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Decoupling analysis of Maglev Variable Stiffness Joints Based on Permanent Magnet 7

Decoupling Analysis of Maglev Variable Stiffness Joints Base...

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7th international conference on robotics, Control and Automation Engineering, RCAE 2024

作者： Luo, Kang Zhai, Mingda Chen, Jianbin He, Chengtao Li, Xinwei Zhang, Ming Dept. College of Intelligence Science and Technology National University of Defense Technology Changsha China Dept. School of Mechanical Engineering Shenyang University of Technology Shenyang China

ISBN: (纸本)9798350355642

Variable stiffness joints, due to their variable stiffness feature, have promising application prospects in fields such as human rehabilitation and military surveillance. However, currently, variable stiffness joints generally have problems of weak nonlinearity and difficulty in decoupling. Based on this and previous related work, the paper proposes a novel maglev variable stiffness joint, which contains permanent magnet repulsion force that provides a nonlinear property similar to that of the human elbow. And through structural and static research, a decoupling analysis method of joint stiffness and rotational angle is proposed. The research not only provides a technical path for the hominine nonlinear characteristics of variable stiffness joints but also provides theoretical support for the subsequent control of maglev variable stiffness joints. ©2024 IEEE.

关键词： Permanent magnets

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Kinematic Modeling and analysis of Robotic Axial Tilt Errors 17th

Kinematic Modeling and Analysis of Robotic Axial Tilt Errors

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17th international conference on Intelligent robotics and Applications

作者： Feng, Xinyu Zhang, Xu Tu, Dawei Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China

ISBN: (纸本)9789819607709;9789819607716

Collaborative robots boast high flexibility, reliable safety, and strong human-machine collaboration capabilities. However, in practical operations, axis tilt errors can lead to decreased end-effector positioning accuracy, thereby affecting work performance and quality. To address this issue, this paper presents a kinematic model for collaborative robots that integrates Denavit-Hartenberg (DH) parameter errors with axis tilt errors. Initially referencing the DH method, the model establishes both the robot's kinematic model and a parameter error model. It addresses issues unresolved by traditional non-geometric error compensation methods, namely the inability to establish a mapping relationship between the axis tilt joint positions in the calibration coordinate system and the end-effector positional errors. By utilizing the DH method and incorporating a generalized error matrix model, an improved kinematic model that includes tilt errors is proposed. This paper conducts forward kinematic analysis and employs the Newton-Raphson iteration method for inverse kinematics solutions. Simulation and experimental results demonstrate that, regardless of the influence of the tilt error matrix, the model accurately and effectively determines the end-effector pose and joint angles of the collaborative robot.

关键词： Collaborative robot axis tilt error error model kinematics

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