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Trustworthy Artificial Intelligence and Automatic Morse Code Based Communication Recognition with Eye Tracking

Journal of Mobile Multimedia 2023年第6期19卷 1439-1461页

作者： Medichalam, Krishnakanth Vijayarajan, V. Kumar, V. Vinoth Iyer, I. Manimozhi Vanukuri, Yaswanth Kumar Prasath, V.B. Surya Swapna, B. School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore 632014 India Department of Computer Science and Engineering East Point College of Engineering and Technology India Department of Electrical Engineering and Computer Science University of Cincinnati 45221 OH United States Department of ECE Dr MGR Educational and Research Institute Chennai 95 India

Morse code is one of the oldest communication techniques and used in telecommunication systems. Morse code can be transmitted as a visual signal by using reflections or with the help of flashlights, but it can also be used as a non-detectable form of communication by using the tapping of fingers or even blinking of eyes. In this paper, we develop a computer vision based approach that automatically characterizes the characters conveyed wherein a person can communicate to system or another person through Morse code with eye gestures. We can decode this visual eye tracking based language with the help of our automatic computer vision driven method. Our approach uses a normal webcam to detect the gestures made by the eyes and are interpreted as dots and dashes. These dots and dashes are used to represent the Morse code-based words. Image processing techniques-based blink and pupil detectors are employed. Blink detector helps us to detect a blink and the time that took for each blink. A blink that takes 2 to 4 seconds is acknowledged as a dot whereas a blink that takes more than 4 seconds is represented as a dash. The pupil detector helps us to detect the movement of the pupils, and if pupils move towards right with respect to a person then it is acknowledged as next letter and if the pupils are moved towards left with respect to a person then it is acknowledged as next word. In this way, we decode the Morse code which will be communicated using eyes and establish a non-detectable communication between a person and an automatic system. Our experimental results on an unconstrained visual scene with preliminary greeting words indicate the promise of an automatic eye tracking based system with success rate of 98.25% that can be of use in non-verbal communications. © 2023 River Publishers.

关键词： blinks communication eye detection face detection gestures image processing Morse code

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Anomaly Detection in Surveillance Videos Using Deep Learning and SVM Based Data Reduction Method 5

Anomaly Detection in Surveillance Videos Using Deep Learning...

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Hareesh Narayan, B.K. Chowdhury, Abishi Shukla, Pankaj School of Computer Science and Engineering Vellore Institute of Technology Chennai India School of Advanced Science Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350383522

Anomaly detection in video data is a crucial subject that has gained a significant research implication in computer vision with several real-time applications. The researchers worldwide developed innovative solutions in this context in the diverse areas of research specific practical applications. This paper emphasizes over the importance of anomaly detection in a public environment along with its applications for the same. A brief survey of prominent existing techniques with a comparative analysis has been presented in this paper in order to highlight the relevant techniques, available datasets, considered metrics for analysis, and future scope of improvements. In this context, deep learning (DL) approaches like Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks are prominently used for anomaly detection. In this paper, Support Vector Machine (SVM) along with convolution 2D LSTM based data reduction approach is presented which is used to keep only the important data over incremental addition of the data. The experimental analysis, performed on benchmark dataset DCSASS, shows the efficacy of the proposed approach when compared with state-of-the-art approaches as it maintains significant accuracy while ensuring effective data reduction. Furthermore, the proposed approach demonstrates the training and validation loss analysis. It reduces the errors as time progresses which is directly proportional to the incremental addition of data. © 2024 IEEE.

关键词： Accuracy Anomaly Detection Dataset Deep Learning Long Short-Term Memory Support Vector Machine

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Dynamic Clustering for Federated Learning: A Reinforcement Learning Approach to Minimize Time Divergence 1

Dynamic Clustering for Federated Learning: A Reinforcement L...

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1st International Conference on Software, systems and information technology, SSITCON 2024

作者： Tiwary, Shresth Singh, Shaarang Srinivasan, Kathiravan Vellore Institute of Technology School of Computer Science and Engineering Vellore632 014 India

ISBN: (纸本)9798350352931

Federated learning (FL) offers a decentralized approach to training machine learning models, allowing data to remain on local devices and preserving privacy. However, the decentralized nature of F Lintroduces challenges such as heterogeneous device performance, leading to straggler devices that slow down the training process. Traditional clustering methods, whether static or dynamic, often fail to adapt effectively to these variations. To address this, the paper proposes FedDy, an advanced algorithm incorporating reinforcement learning (RL) and hybrid clustering techniques. FedDy begins with k-means clustering and dynamically selects the optimal clustering method in each round, guided by RL. Silhouette analysis helps determine the optimal number of clusters, while a hybrid metric considers upload times, computation times, and model divergences to ensure balanced clusters and efficient training. The experiments on the Fashion MNIST dataset demonstrate that FedDy reduces training time by 69.1 %compared to FedAvg, with a similar accuracy of 90.27. The enhanced version, FedDy_Enh, further reduces training time by 65.8% compared to FedAvg and 32.3% compared to FedStat, achieving the highest accuracy of 90.74%. © 2024 IEEE.

关键词： Federated learning

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Advanced Strategies for Detecting Ransomware Threats 9

Advanced Strategies for Detecting Ransomware Threats

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9th International Conference on Communication and Electronics systems, ICCES 2024

作者： Santhi, H. Sathish, Nalagatla Akash, Daddala Reddy Sai, Vidivada Chowdary Adithya Ganesh, Peddineni Sai Venkata Madhira Reddy, Yashwanth School of Computer Science and Engineering Vellore Institute of Technology TamilNadu Vellore632014 India

ISBN: (纸本)9798350377972

Ransomware is one of the key threats that have been created to lock the important services and data. New techniques like machine learning and blockchain are being used for enhancing the detection and mitigation process. However, these continue to face major challenges in terms of time lags arising out of delayed technology adoptions, gaps in security protocols, and inaccessibility of certain detection mechanisms within the systems to identify real-time advanced ransomware. In addition, fast restoration and ensuring minimum downtime for operations is still difficult. tackling these challenges by the integration of Machine Learning with traditional security techniques to enable early threat detection, accurate mitigation strategies, and quick restoration. Besides, it employs machine learning toward the correct identification of ransomware behavior and continuous adaptation to developing threats. The goal is to develop a hard, anticipatory defensive system that incurs the least possible blow from ransomware, thereby focusing on future research directions to better perfect such technologies. © 2024 IEEE.

关键词： Restoration

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A Comprehensive Study on Performance of Serial and Parallel Web Crawlers 3

A Comprehensive Study on Performance of Serial and Parallel ...

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Parajuli, Elina Devi, K. Vimala Prashanth, Narayanan Bashyal, Ashutosh School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9798350361186

Web crawlers, also known as web spiders or web robots, are automated programs that systematically browse the World Wide Web, indexing web pages and gathering data for various purposes. This paper addresses the inefficiency of default Python crawlers, caused by the Global Interpreter Lock (GIL), in the context of web page collection for search engines. It aims to create a concurrent Python crawler and compare its performance with a single-threaded counterpart. The crawler will undergo three iterations: a sequential version, a concurrent version using thread pool executor, and an aiohttp version for concurrent requests. Performance metrics such as speed of retrieval, internal processing, and memory requirements will be analyzed. The goal is to develop an efficient Python crawler for continuous web crawling, providing insights for developers and users, and comparing Python's performance with another programming language. © 2024 IEEE.

关键词： Python

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Visual Impairment Navigation: Real-Time Contour Mapping with 3D Spatial Audio Feedback 8

Visual Impairment Navigation: Real-Time Contour Mapping with...

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8th International Conference on Electronics, Communication and Aerospace technology, ICECA 2024

作者： Kanagaraj, R. Agarwal, Archit Baurai, Archit Jain, Devyansh Singha, Saptak Baliyan, Subhanshu Vellore Institute of Technology School of Computer Science and Engineering Tamil Nadu Vellore India

ISBN: (纸本)9798350367904

To help the visually impaired navigate through their environment in real time, this research study proposes a novel navigation system. This navigation system works on various navigation algorithms for contour mapping, computer vision techniques for visual processing and deep learning models implemented using TensorFlow for obstacle recognition, OpenCV for real time visual input processing and Open AL for spatial audio mapping. All these technologies combine to create the 'follow the beep' feature in integration with Unity 3D. While designing this navigation system factors such as user experience and navigation efficiency have been considered and therefore conventional methods have been implemented to do so. © 2024 IEEE.

关键词： Mapping

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AI-Optimized Irrigation for Sustainable Agriculture

AI-Optimized Irrigation for Sustainable Agriculture

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2024 International Conference on Advances in Data engineering and Intelligent Computing systems, ADICS 2024

作者： Hussain, Mansoor Karthikeyan, N. Maurya, Ipsit Sinha, Subhratha School Of Computer Science And Engineering Vellore Institute Of Technology Chennai India School Of Electornics And Engineering Vellore Institute Of Technology Chennai India

ISBN: (纸本)9798350364828

This paper presents an innovative AI-enhanced irrigation system designed to optimize water management in agriculture. The system integrates advanced technologies such as IoT, sensor networks, and artificial intelligence algorithms to achieve precise and efficient irrigation scheduling. Leveraging real-time data from sensors including soil moisture, temperature, and humidity, combined with historical weather forecasts, the system employs a dynamic algorithm to make informed irrigation decisions. Experimental evaluation conducted over a week-long period using a garden rose as a test subject demonstrated the system's ability to maintain optimal soil moisture levels within the range of 60-75%, while significantly reducing water consumption compared to conventional methods. Simulation results further validated the system's effectiveness in predicting soil moisture levels and optimizing irrigation scheduling. Key metrics including enhanced crop output, reduced water usage, and adherence to sustainable farming practices were used to assess the superiority of the proposed model. Overall, the AI-enhanced irrigation system presents a promising solution for sustainable agriculture, offering improved water conservation, enhanced crop productivity, and efficient resource utilization. © 2024 IEEE.

关键词： Water conservation

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Enhancing Mobility with Next-Generation Partial Hand Prosthesis Using Arduino Uno and Flex Sensors 2

Enhancing Mobility with Next-Generation Partial Hand Prosthe...

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2nd International Conference on Cyber Physical systems, Power Electronics and Electric Vehicles, ICPEEV 2024

作者： Matury, Sai Sathwik Sam Stewart, X. Ra, Nawin Kumba, Krishna School of Computer Science & Engineering Vellore Institute of Technology Chennai India School of Electrical Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350388664

The proposed work delves into the comprehensive design, development, and evaluation process of a 3D printed prosthetic arm, employing servo motors controlled by an Arduino Uno microcontroller to enable gesture mimicry through flex sensors integrated into a wearable glove. The primary objective is to provide an affordable and accessible solution for individuals with upper limb disabilities. The paper outlines the intricacies of the design process, system architecture, programming nuances, and rigorous testing procedures, showcasing promising results in terms of gesture accuracy, adaptability, and user-friendliness. The prosthetic arm demonstrates high precision in replicating various hand gestures. Future work will focus on enhancing the durability and responsiveness of the system to further improve its practical application. User feedback has been overwhelmingly positive, indicating significant potential for real-world adoption. © 2024 IEEE.

关键词： Servomotors

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Smart Hybrid Mini-Xception Model and Eyebrow Displacement-Based Stress Level and Emotion Detection System 12th

Smart Hybrid Mini-Xception Model and Eyebrow Displacement-Ba...

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12th International Conference on Recent Trends in Computing, ICRTC 2024

作者： Bhuvana, S. Anantha Prabha, P. Deva Priya, M. Christy Jeba Malar, A. Karthick, S. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Department of Computer Science and Engineering PSG Institute of Technology and Applied Research Tamilnadu Coimbatore India Department of Computer Science and Engineering Karpagam College of Engineering Tamilnadu Coimbatore India Department of Information Technology Sri Krishna College of Technology Tamilnadu Coimbatore India Department of Computer Science and Engineering Delhi - NCR Campus SRM Institute of Science and Technology Uttar Pradesh Ghaziabad India

ISBN: (纸本)9789819789450

Stress is a state of mental or emotional strain due to adversative or challenging situations. A human may undergo bad life experiences or events, and it is a significant issue to be dealt in today's society. It comes as a result of family situations, health concerns, work environments and people's behavior among other things. It affects people of various ages, including children, teenagers, middle-aged people and senior citizens. It has serious consequences affecting human body and life. These problems can be addressed by detecting mental stress at an early stage. The main goal of the propounded system is to identify human stress using a pre-trained Mini-Xception model. Additional measures such as eye moments, mouth activity and head motion are employed for determining the level of human stress. FER2013 dataset is used and the system is tested for all kinds of emotions. Human stress level is experimented by capturing video using webcam. From the experimental outcomes, it is evident that the proposed system offers better performance in terms of Precision, Accuracy, Specificity and Sensitivity in contrast to traditional methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Eyebrow displacement FER2013 dataset Mini-Xception model Stress detection

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Model of Sentiment Analysis in Different Platforms on Social Media 4

Model of Sentiment Analysis in Different Platforms on Social...

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4th International Conference on Soft Computing for Security Applications, ICSCSA 2024

作者： Vasanthi, P. Madhu Viswanatham, V. Vellore Institute of Technology School of Computer Science and Engineering Tamil Nadu Vellore India

ISBN: (数字)9798331515720

ISBN: (纸本)9798331515720

Reviews provide useful information for making decisions. Online stores allow customers to express their opinionson goods and services. Many of these opinions are available tothe public as reviews. Customer reviews are very interesting to manufacturers, retailers, and customers. Such reviews are valuable to consumers since they help them choose which brand or product to purchase. These subjective reviews can help manufacturers identify areas where their product needs improvement. Because there are so many reviews available online foranalysis, manually reading them is not cost effective. An automated system that offers a summary of user sentiments is required to optimize this laborious task. Sentiment analysis is a branch of study that examines how reviews and opinionated literature reflect the sentiments or opinions of readers. In the process of sentiment analysis, machine learning, deep learning, and optimized algorithms are used to assess sentiments and emotions and generate a distilled output for use in decision making. © 2024 IEEE.

关键词： Adversarial machine learning

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