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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

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HexHeAd: 6D Head Pose Estimation Based Visual Focus of Attention detection 3

HexHeAd: 6D Head Pose Estimation Based Visual Focus of Atten...

引用

3rd international conference on Robotics, Automation and Intelligent Control, ICRAIC 2023

作者： Wan, Zhitao Fei, Haoze Xu, Yuanwei Yang, Shenjia Yang, Miao Hua, Xiuping University of Nottingham Ningbo China and Ningbo Free Trade Zone Blockchain Laboratory Ningbo China Nottingham University Business School China University of Nottingham Ningbo China Ningbo China

ISBN: (纸本)9798350360813

This paper proposes a visual focus of attention detection method based on the user's 6D head pose estimation, which determines the content of the observer's visual focus of attention according to the current visual attention focus range of the observer. The system detects the observer's current head posture and uses continuous tracking of the direction of interest to determine when the observer's visual focus of attention is drawn to a specific location and content. Context-based visual focus of attention span is used as an approach to detect the level of interest an observer has in a particular content. Then, according to the level of interest of the observer, a visual focus of attention-based interaction channel can be established, and the observer's feedback on specific content can be accumulated to obtain the relevant preferences of the observer and establish a foundation for future interactions. In order to evaluate the method, we conducted an experiment using short video as the target visual focus of attention, and when the observer watched a large screen playing specific content in an open area, the proposed method determined the current visual focus of attention level of the observer, and further discovered the interest of the observer according to the content viewed by the observer. The evaluation results show that our approach has good performance for automatic observer tracking or human-robot interaction. © 2023 IEEE.

关键词： Behavioral research

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Defect detection of vaccine glass tubes based on semantic segmentation 3

Defect detection of vaccine glass tubes based on semantic se...

引用

3rd international conference on Artificial intelligence and Computer Engineering, ICAICE 2022

作者： Ji, Qingbo Wu, Jiangjiang Kong, Deqiang Zhang, Lei Hou, Changbo College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin Engineering University Harbin150001 China

ISBN: (纸本)9781510663473

Glass tubes for vaccines have strict production requirements, and large-scale production is difficult to ensure their high quality. Minor damage or defects may seriously affect the quality of vaccines. In the actual task of vaccine glass tubes defect detection, there are many kinds of defects, and the defect forms of the same kind are also very different. Traditional manual detection is time-consuming, laborious and expensive. The traditional digital image processing algorithm is also poor in the field of defect detection. This paper proposes a DD-STDC net (STDC net for defect detection) based on semantic segmentation. Multi-scale input branches are introduced on the basis of the original STDC net, so that the model can learn the regional relationship between different scales through attention. For all kinds of irregular defects, deformable convolution is used in the backbone to capture the edge details of irregular objects more easily. The attention mechanism is embedded in the backbone network to strengthen the attention to the effective spatial location and the effective semantic information channel. On the test set, we achieve 66.3% MIOU on NVIDIA RTX 2060Super, which is 1.55% higher than the STDC net. © 2023 SPIE.

关键词： Convolution

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Optimization of Hough's algorithm based on ink layer detection 3

Optimization of Hough's algorithm based on ink layer detecti...

引用

3rd international conference on Mechanical Design and Simulation, MDS 2023

作者： Wang, Meiou Wu, Shuqin Zhuang, Yanyan Chang, Kun Wang, Yiming Liu, Haohong Department of Mechanical Engineering Beijing Printing Institute Beijing102600 China Beijing Key Lab. of Digitalized Printing Equipment China National Printing Machinery Quality Inspection and Testing China

ISBN: (纸本)9781510664890

The current method of detecting ink layer thickness still has the disadvantages of slow speed, will produce wear and tear on the detection object, low accuracy, etc. For this reason, this paper proposes an optimized Hough algorithm detection method for the existing ink layer thickness detection method. Firstly, based on the triangular laser principle, the measurement image is captured by CMOS camera;secondly, the probabilistic Hough linear transformation algorithm based on vertical straight line is optimized;finally, the system calibration and accuracy measurement are completed. The maximum detection thickness of the algorithm optimization reaches 20µm, and the detection accuracy is better than 3µm, which verifies the feasibility of the algorithm optimization. © 2023 SPIE.

关键词： Computer vision

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Phishing URL detection and Reporting system Using Machine Learning Approach 3

Phishing URL Detection and Reporting System Using Machine Le...

引用

3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Aman, D. Reddy, J. Kartheek Sai, B. Manoj Dhanalakshmi, D. Hariharan, Shanmugasundaram Kukreja, Vinay Vardhaman College of Engineering Department of Cse Hyderabad India Chitkara University Institute of Engineering and Technology Department of Computer Science and Engineering Punjab India

ISBN: (纸本)9798350342338

Phishing attacks continue to pose a threat to the internet users due to the consequences they bring, including the compromise of sensitive information, financial harm and reputational damage. In this research paper, we propose to create a free access, ad-free and non-profit website that uses machine learning algorithms to identify phishing URLs. This website shall be designed to provide users with a reliable and user-friendly tool to evaluate the legitimacy of the URLs they come from. Using different data-sets containing phishing and legitimate URLs, extract important features to train the classification model. The model will be embedded in website, which will evaluate user-submitted URLs and provides true phishing detection. There exists report, which claims on the website where users can contribute to the collective fight against phishing attacks by reporting phishing URLs they encountered. In this way users actively contribute to the development of the and improved efficiency of the system. © 2023 IEEE.

关键词： Ad-free Platform Cyber Security Machine Learning Non-Profit Organization Phishing detection Reporting system URL Analysis

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A Deep Learning-Based Method for HTTP Payload Classification in Attack detection 3

A Deep Learning-Based Method for HTTP Payload Classification...

引用

3rd international conference on Green Communication, Network, and Internet of Things, CNIoT 2023

作者： Zhu, Ming Hong, Tao Luo, Qinglan Shang, Xia School of Computer Science and Technology Donghua University Shanghai201620 China Shanghai Moule Network Technology Co. Ltd. Shanghai201620 China

ISBN: (纸本)9781510668867

Attack detection is a crucial process that involves closely monitoring and identifying malicious attacks. To identify and locate such attacks with precision, there is a need for a thorough analysis and classification of malicious payloads. To this end, a deep learning-based method is proposed in this paper, which enables the efficient classification of payloads for attack detection. The method involves segmenting the payloads using regular expressions, which helps in preserving their syntactic structure. Also, an improved TF-IDF algorithm is introduced to construct a streamlined vocabulary that alleviates the slow training problem caused by a large vocabulary. By fusing the features of vectors extracted using CNN and BiLSTM-Attention, the payload content can be effectively represented, yielding more accurate recognition results and improving the problem of low detection accuracy associated with traditional methods. The experimental results reveal that the proposed method achieved an accuracy of 99.21% on the CSIC 2010 dataset, which is significantly higher than that of the traditional method, and has faster training speed. This suggests that the proposed method can detect more stealthy attacks and build a more effective Web attack detection system. © 2023 SPIE.

关键词： Deep learning

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Dynamic SLAM system Based on Object detection 3

Dynamic SLAM System Based on Object Detection

引用

3rd international conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Shan, Dongri Li, Jiamin Wang, Xiaofang Zhang, Peng Jinan250300 China Jinan250300 China

ISBN: (纸本)9781510667563

Simultaneous Localization and Mapping (SLAM) is a key technology in robot field. Aiming at the problem that traditional SLAM system has low localization accuracy in high dynamic scene, this paper proposes a visual SLAM system combining object detection in dynamic environment. Firstly, the potential moving objects in the image are located in the object detection boxes, and the feature points belong to the moving objects are filtered out. Then, the possible residual dynamic points in the environment are thoroughly filtered by combining the optical flow method. Finally, the pose of the system in the dynamic environment are estimated by using the static objects and the remaining feature points in the background. Using TUM RGB-D datasets for experiments, the results show that compared with ORB-SLAM2, the pose estimation accuracy of the improved system is improved by 90% on average under high dynamic scenes, and the positioning accuracy is also significantly improved compared with the classical dynamic visual slam system DS-SLAM. © 2023 SPIE.

关键词： Object detection

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Research on Digital Twin Testing Theory and technology for Intelligent Connected Vehicle 3

Research on Digital Twin Testing Theory and Technology for I...

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3rd international conference on Artificial intelligence, Virtual Reality, and Visualization, AIVRV 2023

作者： Jiang, Huajun Dong, Hongliang Zhang, Yuan Fang, Zhiyi Taizhou Vocational and Technical College 788 Xueyuan Rd Jiaojiang District Zhejiang Taizhou China Jilin University No.2699 Qianjin Street Changchun City China

ISBN: (纸本)9781510671485

Due to the difficulty and high cost of conducting sufficient real-world road tests, it is widely accepted in the industry to use a digital twin testing system that combines virtual simulation testing with real-world road testing to test and evaluate autonomous driving systems. Digital twin testing can simulate a road test environment using technologies such as sensor simulation and vehicle dynamics simulation, advanced graphics processing, traffic flow simulation, digital simulation, and road modelling. We integrated simulation testing tools, V2X communication devices, and real testing vehicles to achieve digital twin autonomous driving testing based on virtual simulation and real environments. It generates scene data based on virtual scene simulation software, constructs simulated scenarios mapping to reality, and uses V2X communication devices to transmit simulated scene environment data in real time to the real testing vehicles. It also receives real-time status data from the vehicles and feeds them back to the scene controllers, enabling autonomous vehicles to test different scenarios on real roads. In active safety-related testing, virtual scenes can avoid accidents and save unnecessary equipment losses. The system has high repeatability, and after a large number of repetitive in-vehicle tests, it can significantly reduce functional defects in the tested system, reducing the workload of actual vehicle field testing and road testing and improving testing efficiency and cost savings. © 2023 SPIE.

关键词： Autonomous vehicles

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Structured Fourier Contour Embedding for Arbitrary-shaped Slender Text detection 3

Structured Fourier Contour Embedding for Arbitrary-shaped Sl...

引用

3rd international conference on Artificial intelligence, Virtual Reality, and Visualization, AIVRV 2023

作者： Chen, Jianyong Liang, Lingyu Xiao, Wocheng South China University of Technology Guangzhou China Guangzhou China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing China

ISBN: (纸本)9781510671485

Arbitrary-shaped text detection is a challenging task where a text instance representation should be well designed to cover diverse text geometry variances. Most of current methods represent text instances as image mask or contour point sequences, but they might lead to expensive post-processing or restricted capability of shape modeling. Most recently, Zhu et al. proposed Fourier Contour Embedding (FCE) method to represent arbitrary shaped text contours in the Fourier domain, and constructed FCENet to obtain state-of-the-art (SOTA) performance. However, even the FCE signature and FCENet may suffer significant detection performance degradation on slender-shaped text instances like most other text detectors because of the mismatch between the square-shaped receptive fields and the large aspect ratio of arbitrary-shaped slender text}. To tackle this problem, we designed Structured Fourier Contour Embedding (Structured-FCE) to encode both instance-level features and local geometric features of the boundaries. Then, we constructed Structured-FCENet to predict and merge Structured-FCE signatures to construct the boundaries of arbitrary-shaped slender texts. Qualitative and quantitative results illustrate that Structured-FCENet obtain SOTA performance on CTW1500, Total-Text and DAST1500 benchmark datasets, especially for the challenging slender text instances of various shape. © 2023 SPIE.

关键词： Computer vision

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Autism Spectrum detection Using 3D CNN 3rd

Autism Spectrum Detection Using 3D CNN

引用

3rd international conference on Machine Vision and Augmented intelligence, MAI 2023

作者： Ganeshan, Harini Suresh, Chalumuru Annireddy, A. Pamidimukkala, Chandralekha Alleni, Supraja Department of CSE VNR Vignana Jyoti Institute of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9789819743582

Autism Spectrum Disorder (ASD), a form of neurological sickness, appears in youngsters among 6 and 17 years of age and impacts conversation abilities and social conduct. ASD impacts social interactions and communication and reasons repetitive behaviors in patients. Consistent with the WHO, ASD impacts one baby in one hundred sixty. Early diagnosis during adolescence is critical and might improve the social capabilities and communiqué problems of youngsters. So, it is very important to find a proper way to detect Autism. For diagnosing neurological diseases, it is highly required to study the structural vicinity relationships within the brain. Hence, to study the brain and its patterns, fMRI (functional magnetic resonance imaging) is used. It detects correlated fluctuations inside the blood oxygen degree-dependent (bold) alerts from the brain regions. This paper is proposed with the primary motive of building, training and testing a 3D Convolutional Neural Network (CNN) model using a dataset abbreviated as ABIDE—Autism Brain Imaging Data Exchange dataset and predict outcome of the class labels as autism or no-autism for unseen health records. The project also aims to present a comprehensive analysis and provide some recommendations related to ASD results generated by the system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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End-to-End Rockfall detection Based on DINO 3

End-to-End Rockfall Detection Based on DINO

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3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial intelligence and Big Data Forum, AIBDF 2023

作者： Liao, Yunping Li, Shichao Yang, Yong Li, Boy Li, Hui Yan, Qi Technology Innovation Center of geohazards automatic monitoring Ministry of Natural Resources Chongqing Institute of Geology and Mineral Resources Chongqing China Southwest University College of Computer and Information Science College of Software Chongqing China School of Civil Engineering Chongqing University Chongqing China

ISBN: (纸本)9798400716362

In this paper, we utilized the DINO object detection model to achieve end-to-end deep learning-based rockfall detection. Rockfalls cause significant economic losses and casualties every year, and timely detection and response are crucial to prevent accidents and reduce human casualties. By detecting a small number of rockfall features in the early stages of a potential rockfall, this study analyzed the severity of the disaster and aimed to protect people’s lives and health by providing critical time to avoid disasters. In this paper, we annotated 2,201 images from 28 confirmed rockfall videos, of which 66.2% were primarily small targets according to the COCO dataset definition. By using the Transformer-based DINO model, we achieved an AP of 43.5%, which outperformed other excellent object detection models, especially in its ability to detect small targets. © 2023 Copyright held by the owner/author(s).

关键词： Object detection

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