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arXiv 2025年

作者： Ijjina, Earnest Paul Joshi, Aniruddha Srinivas Kanahasabai, Goutham Department of Computer Science and Engineering National Institute of Technology Telangana Warangal506004 India B.Tech. Department of Computer Science and Engineering National Institute of Technology Telangana Warangal506004 India

One of the basic requirements of humans is clothing and this approach aims to identify the garments selected by customer during shopping, from surveillance video. The existing approaches to detect garments were developed on western wear using datasets of western clothing. They do not address Indian garments due to the increased complexity. In this work, we propose a computer vision based framework to address this problem through video surveillance. The proposed framework uses the Mixture of Gaussians background subtraction algorithm to identify the foreground present in a video frame. The visual information present in this foreground is analysed using computer vision techniques such as image segmentation to detect the various garments, the customer is interested in. The framework was tested on a dataset, that comprises of CCTV videos from a garments store. When presented with raw surveillance footage, the proposed framework demonstrated its effectiveness in detecting the interest of customer in choosing their garments by achieving a high precision and recall. Copyright © 2025, The Authors. All rights reserved.

关键词： Sales

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Recommendation of Personalized Learning Path in Smart E-learning Platform Using Reinforcement Learning Algorithms 8th

Recommendation of Personalized Learning Path in Smart E-lear...

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8th International Conference on Inventive Communication and Computational technologies, ICICCT 2024

作者： Deepa, S. Arunkumar, M.S. Kanimozhi, T. Eswaran, balamurugan Duraivelu, Vivek Sweatha, M. Department of Computer Technology-PG Kongu Engineering College Tamil Nadu Erode Perundurai638060 India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai600062 India Department of Computer Science and Engineering Bannariamman Institute of Technology Sathyamangalam India School of Information Technology Texila American University Lilayi Zambia Department of Computer Science and Engineering B V Raju Institute of Technology Telangana Narsapur502313 India Kongu Engineering College Tamil Nadu Erode Perundurai638060 India

ISBN: (纸本)9789819777099

The exponential expansion of e-learning has significantly broadened educational opportunities globally, empowering students to engage in learning experiences from anywhere. However, the abundance of online courses poses a challenge in customization, often resulting in diminished learning outcomes as learners struggle to select suitable courses tailored to their unique requirements. Personalized learning addresses this by adapting activities to individual needs, fostering the development of capabilities and personality. The proposed system integrates Markov Decision Processes (MDPs) and Reinforcement Learning (RL), leveraging deep Q-learning for sequential recommendations and MDP adaptability to tailor learning paths. This combined approach holds promise for revolutionizing e-learning by delivering personalized, adaptive experiences. Learners benefit from tailored courses, activities, and learning paths, optimizing their educational journey. Continuous adaptation and improvement, facilitated by the core MDP framework and user feedback, further enhance effectiveness in e-learning environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Federated learning

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An Innovative Method for Mobile Network Payment Security System based on hybrid LSTM-Ensemble Learning-based Model 3

An Innovative Method for Mobile Network Payment Security Sys...

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： Sujatha, N. Pramod, S. Aravindh, S. babu, balagopala Ramesh Devi, S. Rukmani Ananthi, M. B. M. S. College of Engineering Department of Mathematics Karnataka Bengaluru India Nitte Meenakshi Institute of Technology Yelahanka Department of Mathematics Karnataka Bangalore India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India SRKR Engineering College Department of Computer Science and Engineering Andhra Pradesh Bhimavaram India SIMATS Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Computer Science Tamilnadu Chennai India KGiSL Institute of Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India

ISBN: (纸本)9798350354171

It is common practice in many industries to use cash since it accounts for more than 85% of payments in almost all developing countries. A cell phone is become an everyday item. Mobile phones have practically become people's constant companions due to the plethora of other uses they offer beyond just communicating. Since they are both cheap and multipurpose, soon everyone will be utilizing them. In an ideal world, everyone would use their cell phone for everything. Verification, preprocessing, and training the model are the three parts that make up the method. In order to confirm the payment, the customer's biometric template is checked during the verification procedure. The three stages of fingerprint preparation include matching fingerprint templates, extracting fingerprint minutiae, and fingerprint preprocessing. The training of the model was carried out using a Hybrid LSTM-Ensemble Learning. The average accuracy of the suggested method is 92.76%, which is higher than LSTM and Ensemble Learning. © 2024 IEEE.

关键词： Contrastive Learning

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Development of a Current-Position Control Strategy for Motion Systems Utilizing Nonlinear Reluctance Actuators 63

Development of a Current-Position Control Strategy for Motio...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Al Saaideh, Mohammad Al-Rawashdeh, Yazan M. Alatawneh, Natheer Aljanaideh, Khaled boker, Almuatazbellah Al Janaideh, Mohammad Memorial University St. John's Department of Electrical and Computer Engineering NLA1B 3X5 Canada University of Jordan Electrical Engineering Department at Al-Zaytoonah 130 Amman 11733 Jordan Memorial University St. John's Department of Mechanical and Mechatronics Engineering NLA1B 3X5 Canada Jordan University of Science and Technology Faculty of Engineering Department of Aeronautical Engineering Irbid22110 Jordan Virginia Tech Department of Electrical and Computer Engineering BlacksburgVA24060 United States University of Guelph School of Engineering GuelphON N1G 2W1 Canada

ISBN: (纸本)9798350316339

Reluctance actuators (RA) can replace the current Lorentz actuators in the next generation of positioning and scanning motion systems, such as the wafer stage in lithography machines. However, the nonlinear output force characteristic and the gap dependency of the RA are the main challenges in using the RA to drive motion systems. In this paper, we design a two-loop control approach for a reluctance actuator motion system (RAMS) to achieve tracking performance for a desired motion profile. First, the current control loop linearizes the RA under different conditions. Next, the position control loop is designed using a PID control based on an extended-high gain observer to achieve a desired motion profile considering unknown dynamics in the system. The simulation results show the efficiency of the proposed current control in linearizing the dynamic behavior under different desired forces and nominal air gaps and achieving a frequency response similar to the spring-mass-damper system. Moreover, the position control can achieve different long-stroke and short-stroke motion profiles with different amplitudes and ranges of motion. © 2024 IEEE.

关键词： Proportional control systems

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Real-Time Video Enhancement with Spatio-Temporal Attention via Deep Convolutional Neural Networks 3rd

Real-Time Video Enhancement with Spatio-Temporal Attention v...

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3rd International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Maria, Anto bennet balasubramanian, Swaminathan Vijayan, Rajmohan Sonthi, Vijaya Krishna Ramakrishnan, Jayapratha Manogaran, Umamaheswari Sengan, Sudhakar Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai600062 India Karnataka Bengaluru560069 India Tamil Nadu Chennai602107 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522502 India Department of Information Technology V.S.B. College of Engineering Technical Campus Tamil Nadu Coimbatore642109 India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627451 India

ISBN: (纸本)9789819783540

The realm of video content has witnessed exponential growth, and alongside it emerges the challenge of enhancing video quality efficiently. Traditional techniques, although valuable, often fall short of addressing the intricate details and temporal consistencies required for high-quality video upscaling. Moreover, real-time processing demands methods ensuring accuracy and swift computational speeds. Addressing these challenges, this paper introduces the STA-DCNN. This innovative architecture is rooted in combining spatial and temporal attention mechanisms to produce superior video super-resolution. The Spatio-Temporal Attention Module (STAM) acts as a cornerstone, singling out essential features across frames, while the Deep Convolutional backbone (DCb) intensifies these frames, capitalizing on attention-informed features. Furthermore, the Temporal Memory Unit (TMU) preserves crucial aspects from preceding frames, guaranteeing a seamless video rendition. Empirical tests confirm that STA-DCNN notably surpasses its counterparts, offering an ideal balance of quality and real-time processing. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Spatio-temporal data

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An Ensemble Model to Predict Network Traffic Prediction Model Using Rb Multicast Protocol 7

An Ensemble Model to Predict Network Traffic Prediction Mode...

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7th International Conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Deepa, S. Sathishkumar, P. Duraivelu, Vivek Suguna, R. Arunkumar, M.S. Myleshan, M.b. Kongu Engineering College Perundurai Department of Computer Technology - PG Tamilnadu Erode638060 India Bannari Amman Institute of Technology Department of Computer Science and Engineering Sathyamangalam India B v Raju Institute of Technology Department of Computer Science and Engineering Telangana Narsapur502313 India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamilnadu Chennai-62 India Kongu Engineering College Perundurai Tamilnadu Erode638 060 India

ISBN: (纸本)9798350340600

A Vehicular Ad Hoc Network (VANET) is an effective method for addressing group-oriented services. It is possible to support such services through multicast routing. As a result, packet delivery ratios must be improved, delays must be reduced, and overheads must be reduced. Consequently, multicast routing protocols for VANETs must be stable and reliable. A Receiver based Multicast protocol is proposed in our paper that determines how multicast traffic should be forwarded. In the packet header, Rb Multicast stores a list of destinations. Multicast members to whom this packet is addressed are listed in this destination list. Consequently, there is no need to store tree state at intermediate nodes and no multicast tree is required. According to this study, the objective of the study was to predict network traffic by using the V2R dataset, and to use the receiving packets sent by vehicles to the RSUs as a measure of network activity. Our analysis of network traffic flow resulted in the prediction of network flow. Using ensemble classification metrics, we evaluated the data. Simulated results indicate that the proposed model has a superior performance in terms of execution time and prediction accuracy compared to other algorithms. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Energy Proficient and Dependable Cluster Routing in Wireless Sensor Network

Energy Proficient and Dependable Cluster Routing in Wireless...

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2023 IEEE International Conference on Intelligent and Innovative technologies in Computing, Electrical and Electronics, ICIITCEE 2023

作者： Hemavathi, S. Jeya Ganesan, J. Geetha, G. Kishore Kumar, K. Kohila, R. Sri Sairam Engineering College Department of Computer Science Engineering Tamil Nadu Chennai India Sri Sairam Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India B v Raju Institute of Technology Department of Computer Science Engineering Telangana Hyderabad India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science Engineering Tamil Nadu Chennai India Tamil Nadu Namakkal India

ISBN: (纸本)9781665462631

Huge energy utilization information of structures is created with the improving information technology. The energy utilization information is processed by an energy depletion observing system through the wireless sensor network (WSN). Conventional security approaches can face external attacks. Nevertheless, they cannot proficiently solve interior attacks triggered by the captured nodes. Energy-efficient and Dependable Cluster Routing (EPDC) in WSN. This approach aims to reduce energy expenditure and enhance reliable routing in WSNs. The highest energy and highest available bandwidth are selected as a cluster head (CH). In every cluster, the selected CH has received the observed information from the cluster member and then forwarded it to the bS through a relay node. The forwarder relay node is selected based on the average energy faith and transmission faith during data transmission. The whole faith is greater than the average value that node is selected as a data forwarder from cluster to bS in the WSN. Furthermore, the Path Optimization Algorithm (POA) is used to detect the obstacle and build the obstacle-aware route efficiently. The simulation results explain why the proposed method has better residual energy. In addition, it minimized both the network delay and the packet loss rate in the WSN. © 2023 IEEE.

关键词： bandwidth

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Development of Secure IoT Ecosystems for Healthcare

Development of Secure IoT Ecosystems for Healthcare

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International Conference on Intelligent Communication and Computational techniques (ICCT)

作者： Pranav Shirgur Sandeep Chaurasia B. Tech Computer Science and Engineering Manipal University Jaipur Jaipur Rajasthan Department of Computer Science and Engineering Manipal University Jaipur Jaipur Rajasthan

The Internet of Things (IoT) is a rapidly developing field of technology which entails a network of smart devices connected to each other and the internet. The TATCRb2industry is anticipated to increase by 18% to 14.4 billion active connections in 2022. There will likely be about 27 billion linked IoT devices by 2025 as supply limitations, brought about by the current global semiconductor and chip shortage - loosen and demand quickens. IoT has quickly penetrated the healthcare industry, this paper defines a framework that enables the development of secure and scalable IoT healthcare platforms/applications. These platforms will also allow for secure cloud storage and analysis of patient data, helping professionals recognize latent parameters such as patient behavioral patterns that contribute to an ailment. This ultimately will enable the study of social and economic impact of a particular disease. This will greatly cull the survivorship bias in the health care industry - especially in testing times like a pandemic.

关键词： Industries Economics Cloud computing Ecosystems Medical services behavioral sciences Internet of Things

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Text recognition by air drawing 4

Text recognition by air drawing

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4th International Conference on Computational Intelligence and Communication technologies, CCICT 2021

作者： Patel, Jay Mehta, Umang Panchal, Kevin Tailor, Dev Zanzmera, Devam Pandit Deendayal Energy University B.Tech in Computer Science and Engineering Gandhinagar India

ISBN: (纸本)9781665423922

In this paper, the text drawn by the user in the air is captured by the computer's camera, followed by the identification of that text. So, the video camera will be turned on at the time of capturing the written text. Now the particular object is defined based on its colour to detect a movement done by the user. The colour is captured by the lower and upper bound of HSV (Hue Saturation Value), which finally leads to object detection at every instant. Lastly, the text will be recognized by the trained model. The model is trained by CNN (Convolution Neural Network) with an accuracy of 98.64% (training) and 98.24% (testing). For completion of the project, OpenCV, python programming language, and its libraries are used. This project requires only a camera and a defined object. © 2021 IEEE.

关键词： Python

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Handy Smart Stick: A Guide for Visually Impaired People

Handy Smart Stick: A Guide for Visually Impaired People

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International Conference on Communication and Electronics Systems (ICCES)

作者： Mansi Gupta Aditi Laddha Maahi Chouhan Yashasvi Mishra Vitthal Gutte B. Tech School of Computer Science and Engineering Dr. Vishwanath Karad MIT World Peace University Rajsamand India B. Tech School of Computer Science and Engineering Dr. Vishwanath Karad MIT World Peace University Ichalkaranji India B. Tech School of Computer Science and Engineering Dr. Vishwanath Karad MIT World Peace University Chhindwara India B. Tech School of Computer Science and Engineering Dr. Vishwanath Karad MIT World Peace University Kanpur India B. Tech School of Computer Science and Engineering Dr. Vishwanath Karad MIT World Peace University Pune India

It's a perpetual human quest and a constant effort of science to develop and design equipment and aids to help physically challenged people live their lives independently and confidently. blindness and visual impairment are prevalent disabilities that inhibit the independence of the patient and increase the reliance on family members, friends, and guide dogs for navigation and other daily duties. The proposed work outlines a reliable, low-cost, and power-efficient solution that enables safe and secure navigation for visually impaired people. Many researchers have worked on and proposed solutions to the typical problems, but those works have some shortcomings that are addressed in this study. Existing technologies have not focused on optimizing power consumption and reliability, thereby reducing the life of the system. It is vital to reduce power consumption in order to extend the operating lifetime of devices that use batteries as a power source. A methodology has been put forward to address the crucial concern of a gadget that is left on for an extended period of time without being switched off to improve the overall performance of the system. The IoT is entrusted with taking into account heterogeneous equipment that might be severely constrained by its nature and pose problems in the hardware layer of the system. So methods to make the system reliable, accurate, and resistant to failures are inscribed in this study. Additionally, existing systems aren’t economical compared to the offered features, lack automation, and lack audio feedback, particularly notifying obstacles. This study proposes audio feedback in multiple languages and automates the command execution, thereby making it effortless for impaired people to engage with the product. Also, the present state of technology faces challenges in locating the misplaced stick, which means the person has to be dependent on loved ones, friends, or caretakers to find the stick. The proposed automated and handy Smart S

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