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IPA-3D1K: A large Retail 3D Model Dataset for Robot Picking

IPA-3D1K: A large Retail 3D Model Dataset for Robot Picking

引用

IEEE/RSJ international conference on Intelligent Robots and Systems (IROS)

作者： Lindermayr, Jochen Odabasi, Cagatay Jordan, Florian Graf, Florenz Knak, Lukas Kraus, Werner Bormann, Richard Huber, Marco F. Fraunhofer IPA Dept Robot & Assist Syst D-70569 Stuttgart Germany Univ Stuttgart Fraunhofer IPA Dept Cyber Cognit Intelligence CCI D-70569 Stuttgart Germany Univ Stuttgart Inst Ind Mfg & Management IFF D-70569 Stuttgart Germany

ISBN: (纸本)9781665491907

Robotic applications like automated order picking in warehouses or retail stores, or fetch and carry tasks in hospitals, care homes, or households rely on the capability of service robots to find and handle a specific type of object. These applications are challenging as the set of objects is very large and varies over time. Despite its significance, there is no suitable universal large-scale dataset available from the retail domain, which allows for a principled analysis of all relevant robotics research aspects in that field. Hence, this paper introduces a novel dataset of more than 1,000 retail objects, including color images, 3D scans, and high-resolution textured 3D models of individual objects, synthetic scenes and real settings, which covers the specifics of the retail domain. The dataset was designed to serve researchers in all relevant robotics tasks in retail like 3D reconstruction and object modeling, large-scale object classification and instance detection including incremental learning and fine-grained detection, text reading, logo detection, semantic grounding and affordance detection, grasp analysis and manipulation planning, as well as digital twinning and virtual environments. Based on synthetic RGB images of scenes created from the 3D models, two exemplary use cases are examined in this paper to demonstrate the benefits of the dataset: we evaluate the state-of-the-art incremental object detection method InstanceNet and a few-shot fine-grained object classification method. The results prove the suitability of InstanceNet for incremental object detection on large datasets and are promising for the few-shot object classification system.

关键词： Large dataset

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Data Mining and Cloud Computing for Customer pattern analysis and Value Maximization

Data Mining and Cloud Computing for Customer Pattern Analysi...

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conference on Artificial intelligence and robotics and Asia-Pacific international Symposium

作者： Mohammad Sadegh Sirjani Seyed Amir Mousavi Mostafa Sadeghi Department of Computer Ferdowsi University of Mashhad Mashhad Iran Faculty of Computer Engineering Najafabad Branch Islamic Azad University Najafabad Iran

In the contemporary business landscape, companies are seeking efficient methods to analyze customer behavior and extract actionable insights to foster customer relationships and drive business growth. This paper presents a novel approach that combines the strengths of cloud computing, software engineering, and data mining techniques to analyze customer patterns and optimize the value of the customer life cycle. By employing data mining techniques, including clustering, classification, association analysis, and predictive modeling, businesses can identify customer patterns and behaviors. Through the extensive analysis of customer data, organizations can uncover concealed patterns, preferences, and trends, which facilitate informed decisions regarding customer acquisition, retention, upselling, and personalized marketing strategies, ultimately maximizing the value of the customer life cycle. The integration of cloud computing, software engineering, and data mining enables businesses to leverage advanced analytics and extract valuable insights from customer data. This approach enables organizations to gain a comprehensive understanding of customer patterns and behaviors, thereby facilitating targeted marketing campaigns, personalized customer experiences, and improved customer satisfaction.

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

2023 International Conference on the Confluence of Advanceme...

引用

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

ISBN: (纸本)9798350306088

The proceedings contain 66 papers. The topics discussed include: an innovative simplistic solar powered low-cost dry waste segregator robot;artificial intelligence for better organizational creativity: co-occurrence network analysis towards emerging themes;reduced area search (RAS): an algorithm to optimize path planning of mobile robots;an energy-efficient cluster-based routing protocol techniques for extending the lifetime of wireless sensor network;literature review on network security approaches using machine learning models;live wall: an AI based visual seeker through human tracking;glove rupture detection system using skin impedance;object recognition system for the visually impaired: leveraging ioT and remote server integration;and YOLO V5 deep learning model for dental problem detection.

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Research on Safety Status Recognition Model of Commercial Vehicle Driving Behavior 3

Research on Safety Status Recognition Model of Commercial Ve...

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3rd international conference on Artificial intelligence, Human-Computer Interaction and robotics, AIHCIR 2024

作者： Zheng, Yunshuang Wang, Huajun Wang, Bin Yuan, Pengfei China Auto Information Technology (Tianjin) Co. Ltd Tianjin China China Transport InfoJet Technologies Co. Ltd Beijing China

ISBN: (纸本)9798331534035

Safe driving is related to the life and property safety of drivers, enterprises and other people on the road. The government, enterprises and drivers pay more attention to driving safety. With the development of Internet of Vehicles technology, fleet management considers the concept of active service and conducts driver's safety status identification. For this reason, this paper proposes an analysis model for analyzing driving behavior safety based on Internet of Vehicles data. Firstly, based on Internet of Vehicles data, the driving cycle segments of the driver's driving trip are targeted and divided. Then, combined with methods such as PCA and K-means, a driving safety identification model is established. Finally, the safety and driving style analysis of each driving trip are targeted. Through the analysis of driver's safety behavior, targeted safety training can be carried out for drivers to improve the safety of drivers' driving. © 2024 IEEE.

关键词： component driving behavior Internet of Vehicles principal component analysis secure identification

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Double-frame rate-based cheat detection 3

Double-frame rate-based cheat detection

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3rd international conference on Computer Vision and pattern analysis, ICCPA 2023

作者： Wang, HongXia Yan, XiangYu Li, Hui Xu, Fei School of Big Data and Artificial Intelligence Anhui Xinhua University Hefei China

ISBN: (纸本)9781510667563

The relationship between modern education development and artificial intelligence is getting closer and closer, but the technology of online examination and test detection needs to be improved. Most of the existing technologies are aimed at the comparison of pictures per frame, head detection, limb detection, key part detection, etc., although this effect is ideal, but at the same time the requirements for conditions are high. In this paper, for online exam detection, it is proposed to use face recognition and Euclidean distance combined with Yolov3 to complete the cheating detection. © 2023 SPIE.

关键词： Face recognition

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The dual-channel takeaway sentiment analysis model based on RoBERTa-WWM

The dual-channel takeaway sentiment analysis model based on ...

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2024 international conference on Image, Signal Processing, and pattern Recognition, ISPP 2024

作者： Zhou, Hao Hou, Jin Wu, Tao Li, Xuemei Chen, Yan Mao, Guobin Yin, Huiyang Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science & Engineering Yibin644005 China Sichuan University of Science & Engineering Yibin644005 China

ISBN: (纸本)9781510680425

To facilitate self-examination for businesses and enable government agencies to monitor food safety based on sentiment analysis of takeaway reviews, this paper proposes an RoBERTa-WWM-based sentiment analysis model for the takeaway industry, termed RLMT. The model converts the text expressions in takeaway reviews into dynamic semantic feature representations using the RoBERTa-WWM model. The study integrates the global semantic features extracted by combining BiLSTM (Bidirectional Long Short-Term Memory Network) with the Multi-head Attention mechanism and the local semantic features derived from TextCNN (Text Convolutional Network). The fused features are then processed through a fully connected layer and the Softmax function to obtain the final sentiment polarity. Experimental results illustrate that the RLMT model demonstrates superior sentiment classification performance on the waimai_10k dataset compared to current popular sentiment analysis methods, with precision, recall, and F1 values reaching 93.62%, 92.62%, and 92.62%, respectively. © 2024 SPIE.

关键词： Classification (of information)

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Identification of Potential Prognostic Biomarkers for ESCC Using Single-Cell RNA Sequencing Data analysis 10th

Identification of Potential Prognostic Biomarkers for ESCC U...

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10th Biennial international conference on pattern Recognition and Machine intelligence (PReMI)

作者： Patowary, Pallabi Bhattacharyya, Dhruba K. Barah, Pankaj Tezpur Univ Dept Comp Sci & Engn Tezpur Assam India Tezpur Univ Dept Mol Biol & Biotechnol Tezpur Assam India

ISBN: (纸本)9783031451690;9783031451706

This paper analyses the difference between parental cells and cells that acquired radioresistance using scRNA-seq data and investigates the dynamic changes of the transcriptome of cells in response to fractionated irradiation (FIR) towards the identification of potential biomarkers for Esophageal Squamous Cell Carcinoma (ESCC). The divergence of gene expressions is analyzed in response to FIR and the dynamic changes in differentially expressed genes (DEGs) of KYSE-180 cells with two different cumulative doses of FIR (12-Gy and 30-Gy). We construct several biological networks and observe relative to control (0-Gy), 30-Gy induced higher variability of genes. We identified four hub genes TXN, IER2, PCNA, and CENPF involved in ESCC progression.

关键词： ESCC Biomarkers Esophageal squamous cell carcinoma sc-RNAseq Hub gene Differential expression analysis

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analysis of Age Invariant Face Recognition Efficiency Using Face Feature Vectors 1

引用

4th international conference on robotics, Computer Vision and Intelligent Systems (ROBOVIS)

作者： Hast, Anders Zhou, Yijie Lai, Congting Blohm, Ivar Uppsala Univ Uppsala Sweden

ISBN: (数字)9783031590573

ISBN: (纸本)9783031590566;9783031590573

One of the main problems for face recognition when comparing photos of various ages is the impact of age progression on facial features. The face undergoes many changes as a person grows older, including geometrical changes and changes in facial hair, etc. Even though biometric markers such as computed face feature vectors should preferably be invariant to such factors, face recognition generally becomes less reliable as the age span grows larger. Therefore, this study was conducted with the aim of exploring the efficiency of such feature vectors in recognising individuals despite variations in age, and how to measure face recognition performance and behaviour in the data. It is shown that they are indeed discriminative enough to achieve age-invariant face recognition without synthesising age images through generative processes or training on specialised age related features.

关键词： Age-invariant face recognition Biometric markers Discriminative methods

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The Construction and Experimental Technologies of Anonymous Network analysis and Control Platform 7

The Construction and Experimental Technologies of Anonymous ...

引用

7th international conference on pattern Recognition and Artificial intelligence, PRAI 2024

作者： Zhao, Yue Yang, Bin Tian, Bo Yang, Yarang National Key Laboratory of Security Communication Chengdu610041 China School of Computer and Information Engineering Chuzhou University Chuzhou239000 China College of Physics and Electrical Engineering Kashi University Kashi844006 China

ISBN: (纸本)9798350350890

In view of the shortcomings of low accuracy and high false positive rate in the traditional anonymous network traffic analysis methods, this paper proposes the construction and experimental technologies of the anonymous network analysis and control platform, and adopts the Tor network forced routing mechanism to realize the reverse analysis of the random path selection and proxy data restoration of the anonymous network. Experimental results show that compared with the traditional anonymous network traffic analysis methods, the anonymous network analysis and control platform significantly improves performance, achieving a true positive rate of over 95% for detecting different types of traffic in anonymous networks and a false positive rate of less than 3%. This approach not only reduces the overhead of training the model but also enhances the generalization ability of anonymous network analysis and control. © 2024 IEEE.

关键词： Anonymous networks Deployment methods Finite state machine Forced routing Traffic analysis

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Mapping knowledge landscapes and emerging trends of robotics in healthcare: a bibliometric and visual analysis 5

Mapping knowledge landscapes and emerging trends of robotics...

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5th international conference on Computers and Artificial intelligence Technology, CAIT 2024

作者： Zeng, Jianwen Cao, Shihua Shen, Shiying Liu, Xin Li, Sixie Chen, Juan Hangzhou Normal University School of Nursing Hangzhou China Ministry of Education Engineering Research Center of Mobile Health Management System Hangzhou China Nanchang University School of Nursing Nanchang China

ISBN: (纸本)9798331530891

Objective: This study analyses and evaluates the key contributions and scale of development of robotics in healthcare through literature data mining. Methods: Literature search using Web of Science core databases, covering publications up to July 2024. Visualization and analysis were performed with the help of CiteSpaces (6.3.R1), VOSviewer (1.6.20), and Bibliomentrix. Results: A total of 827 papers were included, published in 441 journals, involving 1,402 institutions in 97 countries and 3,436 authors. The number of papers in this field is on an upward trend, and the number of publications has increased rapidly in the past four years, accounting for 65.6% of the total. Human-Robot interaction, social robots, and the application of robots in the elderly are the research hotspots in this field. Conclusion: robotics in healthcare is developing rapidly, with increasing interest from various countries and institutions, but close collaborative networks have not been formed and partnerships need to be strengthened. At the same time, some challenges need to be addressed to better promote the use of robotics. © 2024 IEEE.

关键词： bibliometrics healthcare robotics visualization

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