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检索条件"任意字段=International Conference on Pattern Analysis and Intelligence Robotics"

共 15862 条记录，以下是401-410 订阅

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3rd international conference on Artificial intelligence, robotics, and Communication, ICAIRC 2023

3rd International Conference on Artificial Intelligence, Rob...

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3rd international conference on Artificial intelligence, robotics, and Communication, ICAIRC 2023

ISBN: (纸本)9789819721993

The proceedings contain 33 papers. The special focus in this conference is on Artificial intelligence, robotics, and Communication. The topics include: Design and Research of UAV Fire Emergency and Intelligent Inspection System in the Valve Hall of Converter Station;Development Overview and Application Prospects of Advanced UUVs;bisporus Mushroom 3D Reconstruction for Digital Twin of Smart Factory;Research on Automatic Music Generation Based on LSTM;specific Emitter Identification Method Based on Aggregation Model with Metric Learning in Complex Field;fake Comment Detection Based on Generative Adversarial Networks;Shipping Risk Assessment Ship Inspection Method Based on Improved YOLOv5;spatiotemporal Prediction of Harmful Algal Blooms Based on Spatiotemporal Attention and Transformer;large-Scale Information Dissemination Algorithm Based on Random Mapping;Smoke Detection in Complex Scenery Using Improved Faster-RCNN;CoT-Enhanced CNN-ViT Fusion with Adaptive Token Learning for Precise Facial Expression Recognition;evaluation Method of Cognitive Level Based on Machine Learning and Wearable Device;ship Image Segmentation Based on Multi-dimensional Information and Feature Fusion;real-Time 6-DoF Object Pose Estimation Network Based on 2D-3D Coordinate Correspondence;traffic Light Detection Based on Deep Learning;robot Navigation Based on Reinforcement Learning: An Overview;active Control Technology of Supply Chain Intelligent Work Robot Based on Speech Enhancement Technology;research on Security Technology of Power Dispatching Data Network Based on Deep Learning;An Improved RRT Path Planning Method Incorporating Deep Reinforcement Learning for Space Multi-arm Robot;a Classification Denoising Algorithm Based on 3D Point Cloud Curvature;Comparative analysis of the Effect of KPCA in PSO-GRU Combination Model.

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analysis of Segmented Spectrograms for Human Activity Recognition via Neural Network 10th

Analysis of Segmented Spectrograms for Human Activity Recogn...

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

作者： Dixit, Avinash Kulkarni, Vinay Reddy, V. V. Int Inst Informat Technol Bengaluru India Ignitarium Technol Solut Pvt Ltd Bengaluru India

ISBN: (纸本)9783031451690;9783031451706

Identification of human activities without intruding into their privacy appeals to the use of radar. The micro-movements of the body parts of any activity induce unique micro-Doppler signatures in the spectrogram. We design two neural network architectures that can effectively identify activities. The networks are designed to have a reduced number of model parameters for their adoption in embedded hardware. To observe the sensitivity of these networks, we verify their performance with varying duration of spectrograms.

关键词： Human Activity Classification LSTM Convmixer

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Performance Evaluation of an IoT Based Dual Axis Prototype Solar Tracker Over Fixed PV Installations 3

Performance Evaluation of an IoT Based Dual Axis Prototype S...

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3rd IEEE international conference on robotics, Automation, Artificial-intelligence and Internet-of-Things, RAAICON 2024

作者： Kawser, Md. Abdullah Gupta, Rittik Das Islam, Zahirul Roy, Kanoge Sarker, Md. Asaduzzaman Hazrat Ali, Md. European University of Bangladesh Dept. of EEE Dhaka Bangladesh

ISBN: (纸本)9798331534400

A clean, quiet, reliable process with minimal environmental impact is the conversion of solar energy to electrical energy. A dual axis solar tracker prototype model is designed to track sun's rotational positions increasing total energy optimization and average output. A dual axis tracker provides more than 30.79% production than a fixed PV system. The annual and monthly energy generation is previously estimated in dual axis tracker that is 20% more than a fixed 1-axis tracker. In proposed prototype, Arduino Uno as central processing unit that controls mechanism in response to inputs from multiple sensors linked with Blynk interface. The interface allows android users to view real-time statistics including electrical parameters from solar PV. Collected data wirelessly sent to the Blynk interface and spreadsheet through an ESP 8266 module which assist to monitor the parameters having several security levels to ensure IoT safety protocol. Average power output of the prescribed model tested 18% better than a static solar PV. Database readings for the prototype were recorded throughout a certain time-period of 9:00 am to 9:45 am. To validate the project model, several tests were performed such as paired t-tests, correlation and normality tests, q-q plots of different electrical parameters. © 2024 IEEE.

关键词： Average output Blynk Dual axis tracker IoT Solar PV Statistical analysis

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Artificial intelligence-Driven Conceptual Framework to Generate Value from the Data in the Banking Industry: A Systematic Review

Artificial Intelligence-Driven Conceptual Framework to Gener...

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2023 international conference on Artificial intelligence robotics, Signal and Image Processing, AIRoSIP 2023

作者： Kristiana, Idha Ranti, Benny Gaol, Ford Lumban Harso Supangkat, Suhono Doctor of Computer Science Binus University Computer Science Department Jakarta Indonesia Faculty of Computer Science Indonesia University Computer Science Department Depok Indonesia Institute of Technology Bandung Faculty of Digital Communications and Hotel & Tourism Bandung Indonesia

ISBN: (纸本)9798350327472

This paper presents a comprehensive analysis of an artificial intelligence-driven (AI-driven) conceptual framework to generate value from the data in the banking industry. The study provides a literature review to investigate the challenges of an AI-driven conceptual framework in the banking industry. Data quality management, data privacy and security, infrastructure capability, data governance and regulatory compliance, and talent and expertise have been identified as challenges. Based on a systematic review of the literature, this paper proposes Exploration, Classification, Protection, and Value (ECPV) and Explore, Understand, Act, and Engage (EUAE) as key parts of a conceptual framework driven by artificial intelligence to get value from data in the banking industry. The ECPV and EUAE address the identified challenges and offer a structured methodology for managing an AI-driven conceptual framework in the banking industry. It emphasizes the exploration of data sources, classification based on sensitivity and relevance, implementation of comprehensive data protection and privacy measures, and value extraction from data using artificial intelligence approaches. By using an AI-driven conceptual framework called Explore, Understand, Act, and Engage (EUAE) for customer-centric analytics, we give customers a full picture of their bank account activity and more control over how they manage their money. This improves customer engagement by giving customers insights and suggestions. © 2023 IEEE.

关键词： Sales

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Enhancing DNA Sequence analysis for Disease Diagnosis and Prediction Using Parallelised Hash-Based Approach 2

Enhancing DNA Sequence Analysis for Disease Diagnosis and Pr...

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2nd international conference on Computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Sreeram, Anusha Bhukya, Raju Department of Computer Science and Engineering National Institute of Technology Warangal India

ISBN: (纸本)9798331530389

DNA sequencing is a critical tool in genetics, helping to identify disease-causing mutations, predict disease risks, screen for genetic diseases, and monitor disease progression. By determining the order of nucleotides that make up DNA, DNA sequencing allows for the identification of genetic information in specific DNA fragments, entire genomes, or complex microbiomes. It has transformed disease diagnosis and treatment and has applications in biotechnology, forensic science, and evolutionary biology. Comparing DNA sequences helps researchers identify genetic disorders, cancers, and antibody repertoires, leading to tailored treatments for individual patients. However, the diagnosis of diseases using DNA requires an efficient algorithm due to the large number of nucleotides in DNA sequences. The hash-based approach, an optimal string pattern-matching algorithm, is used to identify relevant patterns in DNA sequences. This approach has shown significant improvement in speed compared to the single pattern matching approach for finding multiple string patterns and a parallelized approach for hash based using GPU is also proposed. © 2025 IEEE.

关键词： DNA sequences

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analysis on Robotic Based Waste Segregation Techniques Using Artificial intelligence

Analysis on Robotic Based Waste Segregation Techniques Using...

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2024 IEEE international conference on Emerging Technologies in Computer Science for Interdisciplinary Applications, ICETCS 2024

作者： Lahoti, Jayanti Jathin, S.N. Prasad, Mallika Vamshi Krishna, M. Rajeshwari, B.S. B.M.S. College of Engg Dept. of CSE Bangalore560019 India B.M.S. College of Engg Dept. of CSE Bangalore India

ISBN: (纸本)9798350372502

A successful waste management system depends on the process of segregation of garbage. Segregation is essential since different recyclable waste forms are often collected together at the source. To ensure that the correct techniques are used to treat them for recycling, leading to an overall improved recycling rate and reduced landfill impact, they must be segregated into their respective classes. Over the past years, much research has been conducted to devise effective and productive ways to achieve proper segregation for the waste being produced at an ever-increasing rate. Different authors propose various frameworks and methodologies for waste segregation. This paper aims to analyze existing research on different waste segregation techniques that utilize the concepts of robotics and Artificial intelligence. This gives insight to researchers, designers, and professionals in designing the best and most efficient waste management model. © 2024 IEEE.

关键词： Computer vision

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CART-II: Development of Collision Avoidance Robotic Tether with Soft Sensing Capabilities for Underwater Nuclear Inspection Vehicles 9

CART-II: Development of Collision Avoidance Robotic Tether w...

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9th international conference on Automation, robotics and Applications (ICARA)

作者： Al Mhdawi, Ammar K. Wright, Nick Benson, Simon Haroutunian, Maryam Edge Hill Univ Dept Comp Sci & Engn Ormskirk England Newcastle Univ Dept EE Engn Newcastle Upon Tyne Tyne & Wear England Newcastle Univ Dept Marine Engn Newcastle Upon Tyne Tyne & Wear England

ISBN: (纸本)9781665489218

In nuclear inspection environments, a tether cable is used to transfer power and data between the underwater robotic system and the surface control unit. During underwater nuclear inspection, the tether cable can become entangled and loop with the environment such as nuclear waste boxes and objects. The risk of colliding with underwater objects is increased by the presence of more inspection robots underwater, especially if they are equipped with manipulator arms. As a result of the loops and knots around the cable, the inspection process may be affected and the ROV may not be able to perform its job. The present article is an extended development of the previous Collision Avoidance Robotic Tether (CART-I) model [1]. The CART-I system consists of micro thrusters that are attached to the base unit by a tether cable. The micro thrust unit is capable of generating a small amount of thrust that can move the tether away from obstacles in the water, particularly in restricted spaces. The use of light detection technologies such as IR or LiDAR for obstacle detection is not effective underwater due to the complex motion dynamics of the tether underwater and the size of obstacles, which makes it impossible to provide definite identification of the objects within a given time period. In order to provide the surroundings of the micro thrust units with obstacle detection capability, we have developed an autonomous force soft sensor. Additionally, the soft moulded sealed encase was developed for effective force detection underwater, and was experimentally tested in a water tank to validate our proposed design. Simulation and experimental results of the sensor is provided. The overall goal of the CART-II is to provide a smart autonomous vision of obstacle avoidance using soft force sensing capabilities. This paper presents the full kinematic model and the simulation with finite element analysis of the CART-II system with the hardware and physical implementation of the soft sensor

关键词： Tether force sensing conductive Remotely Operated Vehicles (ROV) marine environment thrust nuclear inspection 3D printing

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Advancements and Applications of Artificial intelligence in Various Sectors: From Internet of Vehicles to 6G and Healthcare 4

Advancements and Applications of Artificial Intelligence in ...

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4th international conference on Pervasive Computing and Social Networking (ICPCSN)

作者： Mittal, Amit Pandey, Harsh Arsh, Mohammad Soni, Mukesh Goyal, Himanshu Rai Sharma, Somesh Graph Era Hill Univ Dept Allied Sci Bhimtal Campus Bhimtal Uttarakhand India Graph Era Hill Univ Dept CSE Bhimtal Campus Bhimtal Uttarakhand India Dr DY Patil Vidyapeeth Pune Maharashtra India Dr DY Patil Sch Sci & Technol Pune Maharashtra India Graph Era Deemed Univ Dept Compter Sci & Engn Dehra Dun Uttarakhand India Graph Era Hill Univ SOM Bhimtal Campus Bhimtal India

ISBN: (纸本)9798350386356;9798350386349

This research study explores the diverse application of Artificial intelligence (AI) across various areas, it transforms impact on technological advancement. This survey begins by investing in AI's role in enhancing the efficiency of the Internet of Vehicles through real-time Data collection and edge computing addressing challenges in optimizing edge service. The paper goes into AI's critical contribution to medical diagnosis, disease detection and treatment highlighting applications in breast cancer detection and medical image analysis. The concept of human-AI collaboration is introduced, using the integration of human intelligence with AI to create a hybrid intelligence system. The paper further discusses an ice role in the COVID-19 pandemic from diagnosis to treatment utilizing deep learning techniques and extreme learning machines. This study extends to large-scale, power grid simulation analysis, where AI including deep learning and reinforcement learning significantly improves efficiency and accuracy. The integration of AI into robotics explains the role of teaching, assistant robots and vision-based assessment systems. The concept of smart farming is introduced, showcasing its potential to revolutionize agriculture production. Focusing on maximum PowerPoint tracking techniques for the improvement of efficiency. This study explores applying the artificial immune system of multi-objective optimization with decision-making and introduces the beneficial perturbation network for overcoming continued learning challenges in an Artificial Neural Network (ANN). Satellite communication and the vision of a 6G network are discussed in the integration of AI, IOT and 5G. In the context of the next generation, Smart credit is highlighted in this study and finally concluded by discussing about the challenges in Wireless Sensor Networks (WSN) and the increasing importance of AI.

关键词： Artificial intelligence Medical Diagnosis Smart Farming Communication Education

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analysis of collision stability of wheeled mobile robots in flexible operating environments 24

Analysis of collision stability of wheeled mobile robots in ...

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3rd international Symposium on Control Engineering and robotics, ISCER 2024

作者： Li, Yan Li, Chenglin Li, Yang Hao, Yuzhen Sun, Zhizhou Zhang, Feng State Grid Intelligence Technology Co. Ltd JiNan Shandong250000 China

ISBN: (纸本)9798400709951

This research focuses on the transient dynamic stability evaluation criteria for wheeled mobile manipulators and presents a dynamic model of wheeled mobile platforms based on virtual decomposition theory. A calculation method is proposed to estimate the critical impact force value, followed by experimental testing on the system prototype with a flexible testing apparatus. The experimental results demonstrate the effectiveness of this estimation method in providing reference values for critical impact forces of wheeled mobile manipulators (WMM). © 2024 ACM.

关键词： Virtual environments

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Machine learning techniques during the COVID-19 Pandemic: A Bibliometric analysis 6

Machine learning techniques during the COVID-19 Pandemic: A ...

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6th international conference on pattern Recognition and Image analysis (IPRIA)

作者： Alavi, Meysam Valiollahi, Arefeh Kargari, Mehrdad Tarbiat Modares Univ Dept Informat Technol Tehran Iran

ISBN: (纸本)9798350314557

The Coronavirus pandemic (COVID-19) has encouraged researchers to produce significant scientific research in this field in reputable international citation databases. It is important to constantly identify and assess scientific outputs in order to learn more about the situation. One of the methods used for evaluating scientific research activities is scientometrics, which has many applications in describing, explaining and predicting the scientific status of researchers and research centers in various national and international fields. It also provides efficient methods for monitoring and ranking organizations, researchers, journals and countries. On the other hand, in recent years, the use of various scientometric techniques, including co-word analysis, co-authorship network and scientific network, has been of great help in discovering the direction of researchers' production in scientific domain and its hidden and overt dimensions. One of the most popular areas since the COVID-19 epidemic started, has been research the use of artificial intelligence and especially machine learning techniques in the prediction, diagnosis and treatment of this disease. In this regard, 2659 documents from the PubMed citation database since the start of the COVID-19 epidemic have been reviewed. The findings of this research show that America, China, India and England are the countries that have cooperated the most with other countries. In addition, the results of this research showed that deep learning and CNN had been significantly used in the researchers' studies.

关键词： COVID-19 machine learning techniques Bibliometric analysis Co-word analysis

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