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Generalizable real-time Accelerated Dynamic MRI

Generalizable Real-time Accelerated Dynamic MRI

引用

international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Silpa Babu Wahidul Alam Rushdi Zahid Rusho Sajan Goud Lingala Namrata Vaswani ECE Dept Iowa State University USA BME Dept University of Iowa USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

We introduce a real-time undersampled dynamic MRI algorithm, termed FewShot-AltGDmin-MRI, that is generalizable: works for many different applications and sampling trajectories without any application-specific parameter tuning. FS-AGM-MRI operates in real-time after processing the first short mini-batch, i.e., it can provide a reconstruction of each new image frame as soon as the MRI scan data for that frame arrives. It also provides a second set of improved quality reconstructions after a short delay. We compare our algorithm against many state of the art batch MRI algorithms, including Deep Learning (DL) based ones, on 17 different retrospectively undersampled datasets and two prospective datasets. FS-AGM-MRI is the only approach that provides accurate recovery for all datasets while also being one of the fastest.

关键词： Magnetic resonance imaging Heuristic algorithms Signal processing algorithms Signal processing real-time systems Trajectory Delays Speech processing Image reconstruction Tuning

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A Scalable and Secure Facial Recognition Attendance System Leveraging CNN Algorithms for real-time Accuracy and Efficiency

A Scalable and Secure Facial Recognition Attendance System L...

引用

ieee Students' conference on Electrical, Electronics and Computer Science (SCEECS)

作者： Aakash Kumar Jiya Sharma Renjith P N School of Computer Science and Engineering Vellore Institute of Technology

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

The facial recognition attendance system represents a modern approach to attendance tracking, designed to improve efficiency, accuracy, and security in various organizational settings. Advanced biometric technologies are leveraged to capture and encode facial features, creating unique digital identifiers for each individual. The methodology employs cutting-edge facial recognition algorithms powered by convolutional neural networks (CNNs) with a 99.5% recognition accuracy rate. These algorithms extract and encode facial vectors with sub-millisecond latency, which are then compared in real-time against a secure, encrypted database of preregistered individuals. Upon a successful match, the system automatically records the attendance, ensuring an accurate and efficient process. With an intuitive web interface built on ReactJS and a backend supported by *** and MongoDB, the system provides seamless access to attendance records and administrative functionalities. The entire attendance recording process is optimized for speed, typically completing within two seconds per individual. Additionally, advanced anti-spoofing measures and integration support with existing HR management systems redefine traditional attendance management practices with a scalable, robust, and secure solution. (Abstract)

关键词： Data privacy Accuracy Face recognition Feature extraction real-time systems Vectors Robustness Recording Mobile applications Convolutional neural networks

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Intelligent Anti-Theft System with Automated Spray Control using ESP32 WROOM

Intelligent Anti-Theft System with Automated Spray Control u...

引用

international conference on Communication systems and Network Technologies (CSNT)

作者： Geetha Shanmugam Deepa Balusamy Elamparithi S Vetriselvan R Mourin Praamoth S Department of Computer Science and Engineering Nandha Engineering College Erode India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

This project demonstrates a low-cost anti-theft solution built around the ESP32-WROOM microcontroller, with integrated chemical spray for security. The system is designed to detect unauthorized entry and respond with spraying disinfectant chemicals such as pepper spray, thus ensuring security as well as being effective against attackers. The ESP32-WROOM microcontroller is known for its Wi-Fi and Bluetooth capabilities, which plays a key role in providing real-time monitoring and control. Users can also access the system via mobile or web applications. In case of any abnormal situation, the user will be notified immediately. This hospitality provides a living environment for its users. Therefore, they can move with peace of mind and even safeguard their valuable things from anywhere. This system also has a modular design that saves energy for easy installation and is suitable for residential, small business and commercial environments.

关键词： Bluetooth Microcontrollers Communication systems Spraying Object detection real-time systems Security Chemicals Wireless fidelity Business

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Unlocking Eye Gestures with Earable Inertial Sensing for Accessible HCI

Unlocking Eye Gestures with Earable Inertial Sensing for Acc...

引用

international Communication systems and Networks and Workshops, COMSNETS

作者： Garvit Chugh Suchetana Chakraborty Sandip Chakraborty Department of Computer Science and Engineering Indian Institute of Technology Jodhpur India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

Eye gestures are widely used in many applications, including device control, biometrics, visual analytics, and health-care, like Alzheimer’s, accessibility, etc. The conventional method for eye gesture detection needs visual information processing devices or smart glasses to capture the movement patterns of the eyeballs. In this paper, we present a novel framework that utilizes inertial measurement unit (IMU) sensors embedded in earable devices for real-time eye gesture detection, which can work as a complementary to visual information processing devices. The framework translates specific eye movements into actionable commands, enabling hands-free interaction for users with limited mobility. Through extensive experimentation with 14 participants across diverse activities such as sitting, walking, running, and driving, the framework demonstrated high accuracy in eye gesture recognition, achieving a macro F1 score of 0.85 on our self-collected dataset.

关键词： Legged locomotion Vocabulary Measurement units Visual analytics Information processing Gesture recognition real-time systems Research and development Intelligent sensors Smart glasses

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Lightweight security Mechanism for IoT applications using Substitution-Box

Lightweight security Mechanism for IoT Applications using Su...

引用

AI in Cybersecurity (ICAIC), international conference on

作者： Fozia Hanif Rehan Shams Urooj Waheed Department of Mathematics University of Karachi Karachi Pakistan Department of Telecommunication Sir Syed University of Engineering and Technology Karachi Pakistan Department of Computer Science DHA Suffa University Karachi Pakistan

ISBN: (数字)9798331518882

ISBN: (纸本)9798331518899

In recent times the use of small computing devices for gathering information from the real world is increasing day by day. The devices like wireless sensors, RIFD tags, embedded devices and IoT devices are required to transmit huge amounts of confidential data for monitoring and controlling. IoT applications have now become an important factor across various industries. That is why the security of IoT device is always been an important issue, because they transmit private and sensitive data. For handling the security issue cryptography is one the way for handling the security issues of IoT devices but sometimes cryptographic algorithms are cracked and as well as very costly. Lightweight cryptography requires less memory and less computational cost. Substitution box is a very useful concept in generating the lightweight cryptographic algorithm that provide robust security in the process of encryption. This study produces lightweight cryptographic encryption and decryption algorithm with the help of substitution boxes. The provided scheme not only provides the encryption procedure but also generating a flexible key structure which enhances the security for IoT devices where lightweight image encryption is crucial. The provided technique will be beneficial for those places where confidential public data has to be secured. The aim of this paper is to recommend effective original and straightforward techniques of encryption and decryption by using the substitution box. Experimental results show the efficiency of the suggested technique in terms of execution time and throughput.

关键词： Wireless communication Ciphers Wireless sensor networks Throughput Encryption Sensors Security Internet of Things S Box Radiofrequency identification

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Design of Automatic Print Defect Detection System Based on Machine Vision Detection Algorithm

Design of Automatic Print Defect Detection System Based on M...

引用

Power Electronics, Computer applications (ICPECA), ieee international conference on

作者： Chao Wang Feiyan Li Zijuan Xu Yunnan Xinhua Printing Factory No. 5 Co. Ltd Kunming China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

In the context of today's digital production, the quality inspection of printed materials has become a key technology to improve printing efficiency and quality of finished products. Especially with the rapid development of the printing industry, the traditional manual inspection method has been difficult to meet the needs of large-scale, high-efficiency production. In order to solve this problem, the automatic inspection system of print defects based on machine vision comes into being, which can not only greatly improve the detection speed and accuracy, but also effectively reduce the labor cost. This paper proposes an efficient defect detection method for printed materials, combining key technologies such as image differencing, binarization, mathematical morphology algorithms, Blob analysis and connectivity analysis to realize automatic identification and classification of minor defects in printed materials. The design and experimental results of the system show that the method has significant advantages in real-time and detection accuracy, and is expected to play an important role in future printing quality control.

关键词： Printing Industries Accuracy Machine vision Morphology Production Quality control Inspection real-time systems Defect detection

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Detection of Brain Tumors from MRI scans using Deep Learning Model

Detection of Brain Tumors from MRI scans using Deep Learning...

引用

international conference on Communication systems and Network Technologies (CSNT)

作者： Yellanuri Surendra S Hupesh Naga Ketan Mohebba Naaz Department of CSE G Pullaiah College of Engineering and Technology Kurnool Andhra Pradesh Department of ECE Ravindra College of Engineering for Women Kurnool Andhra Pradesh

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

The diagnosis of brain tumors dominates the medical sector and great accuracy along with efficiency in their methods to detect the tumor is required. The ability to diagnose brain cancers from MRI data has been greatly aided by recent developments in computer-aided diagnosis (CAD) systems. Recent years have seen improvements in approaches used, for instance with CNN or tumor images being automated. In this work was proposed a model that is based on deep learning using Inception-V3 for the classification and localization of brain tumors. Our model was validated on a publicly available dataset and it was shown that the proposed model is accurate and robust in distinguishing among different kinds of brain tumors. The paper also addresses issues such as data imbalance and model interpretability and the feasibility of integrating the system to be used clinically for real time applications.

关键词： Deep learning Solid modeling Accuracy Magnetic resonance imaging Computational modeling Brain tumors Brain modeling Data models Robustness real-time systems

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Power System Equipment Detection in Thermal Images by Deep Learning Approach

Power System Equipment Detection in Thermal Images by Deep L...

引用

Industrial Electronics: Developments & applications (ICIDeA), ieee international conference on-

作者： Biswojyoti Khandual Rupali Balabantaraya Ashwin Kumar Sahoo Prabodh Kumar Sahoo Sibashis Panda Anushka Parashar Department of Electrical Engineering C.V.Raman Global University Bhubaneswar India Department of Mechatronics Parul Institute of Technology Parul University Gujarat India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

The non-contact accuracy of infrared thermography has made it indispensable for electrical equipment inspection. In order to recognize electrical equipment in thermal pictures, this study presents a revolutionary neural network-based learning model. Based on the neural network algorithm, the proposed work suggests a real-time object detection model YOLO-V8, that can predict the coordinate points, orientation angle, and type of class of certain equipment. To improve accuracy, particularly for small items, the model incorporates an orientation consistency prior. In the proposed work, an extensive thermal imaging dataset of a distribution transformer; covered a range of settings and equipment kinds. According to experimental results, the suggested model achieves a mean average precision of 93.7%, demonstrating its robustness to noise and ability to function at 20 frames per second resulting in accurate detection of different segments of a distribution transformer in a thermal image.

关键词： Deep learning Image segmentation Accuracy Neural networks Object detection Inspection Transformers real-time systems Thermal noise Robustness

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Enhancing Cybersecurity in Medical Cyber-Physical systems Using Blockchain and Deep Learning

Enhancing Cybersecurity in Medical Cyber-Physical Systems Us...

引用

ieee Students' conference on Electrical, Electronics and Computer Science (SCEECS)

作者： Jagdish Pimple Avinash Sharma Department of Computer Sci. & Engineering Madhyanchal Professional University Bhopal

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

Medical Cyber-Physical systems (MCPS) are essential in modern healthcare, enabling real-time patient monitoring, diagnosis, and treatment. However, their integration of digital and physical elements exposes them to cyber-attacks, threatening both patient safety and data integrity. This paper shows a novel cybersecurity framework that combines blockchain technology and deep learning-based intrusion detection to protect MCPS. The proposed model uses a deep DNN-based intrusion detection system (IDS) to categorize medical data as either normal or malicious. Blockchain technology is incorporated to ensure secure, tamper-proof, and decentralized storage of patient information. To improve detection accuracy and reduce false positives, feature fusion techniques, processed through convolutional neural networks (CNNs), are applied. Ethereum-based blockchain ensures that medical data remains confidential and resistant to unauthorized alterations. The system’s effectiveness is validated using a healthcare dataset, showing a marked improvement in detection accuracy, precision, and recall over traditional methods. This integrated solution strengthens the safety and reliability of MCPS, protecting patient data while maintaining efficient data shared between medical devices and healthcare networks. Future research will focus on real-time applications and scaling the model for larger healthcare systems.

关键词： Accuracy Intrusion detection Medical services Cyber-physical systems Feature extraction real-time systems Blockchains Safety Convolutional neural networks Medical diagnostic imaging

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Privacy-Preserving Mechanisms in Resource-Constrained IoT-WSN systems for Healthcare applications

Privacy-Preserving Mechanisms in Resource-Constrained IoT-WS...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), ieee conference on

作者： Gaurav Tuteja Parul Nasra Kanegonda Ravi Chythanya Hasssan MuhamedAle Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

The exponential growth of IoT-enabled healthcare systems has revolutionized patient monitoring and diagnosis through real-time data collection. However, the integration of wireless sensor networks (WSNs) in healthcare introduces significant privacy and security concerns, especially in resource-constrained environments. This paper explores contemporary privacy-preserving mechanisms tailored for IoT-WSN systems in healthcare. Through a critical analysis of recent advancements, we highlight various techniques, their strengths, limitations, and application domains. Our study emphasizes lightweight protocols, secure data aggregation, and end-to-end encryption techniques that address privacy concerns without overburdening system resources. We conclude by discussing open challenges and future directions in designing robust yet efficient privacy-preserving frameworks for healthcare IoT systems.

关键词： Wireless sensor networks Patient monitoring Protocols Federated learning Medical services Data aggregation Robustness real-time systems Security Internet of Things

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