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A transformer based real-time photo captioning framework for visually impaired people with visual attention

Multimedia Tools and Applications 2024年第41期83卷 88859-88878页

作者： Muhammed Kunju, Abubeker Kiliyanal baskar, s. Zafar, sherin A R, bushara s, Rinesh A, shafeena Karim Kerala Kanjirapally India Faculty of Engineering Department of Electronics and Communication Engineering Karpagam Academy of Higher Education Coimbatore India Department of Computer and Electronics Engineering SEST- Jamia Hamdard New Delhi India Department of Electronics and Communication Engineering KMEA College of Engineering Kerala Cochin India Department of Computer Science and Engineering V.S.B College of Engineering Technical Campus Coimbatore India

In recent years, transformer-based photo captioning frameworks plays a crucial role in improving individuals’ overall well-being, self-reliance, and inclusivity by giving them access to visual content via written and voiced explanations. This research investigates a two-layer transformer architecture to capture extensive relationships in visual data effectively. Using a two-layer transformer design, visual attention mechanism enables the model to autonomously identify relevant regions within a picture while generating a particular word within the anticipated caption. To get the features from the images, a pre-trained Inception v3 model is used, and the feature maps are extracted from the final convolutional block. The dataset used in this research was Flick8k, Flick30k, among bespoke datasets. The model was trained on a TPU platform and implemented on a Raspberry Pi 4b graphics processing unit. To assess the efficacy of the two-layer transformer model for photo captioning, a series of experiments were undertaken using benchmark datasets and with state-of-the-art models. The quality of the generated captions was evaluated using quantitative criteria such as bLEU, bLEUR, ROUGE and F1 score. Furthermore, a series of qualitative assessments were conducted, employing human evaluators, to measure the overall coherence, and fluency of the captions. © The Author(s), under exclusive licence to springer science+business Media, LLC, part of springer Nature 2024.

关键词： computer vision

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vegetable supply Chain Using smart Contract 2

Vegetable Supply Chain Using Smart Contract

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Arivarasan, s. Nithish, D. Rahul, P. senthurvel, K. Aravind, venu V.S.B. Engineering College Stream of Computer Science and Engineering Karur India V.S.B. Engineering College R Stream of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

As for therapeutic, ethical and legal restrictions regarding vegetables' accessibility today and concerning registration, matching of the donor-recipient pair, vegetable removal, delivery and transplantation, the needs and challenges vegetable supply and transplantation systems offer today are diverse. This means that to enhance the patient experience and gain their trust, demands for vegetable supply and transplantation that is just and efficient the requires an end-to-end system. Thus, in this study, we give a new solution concept of vegetable supply system which is Decentralized, safe, Transparent, Auditable, Confidential. in vegetable supply and transplantation buyer through sha256 private blockchain. We also list six algorithms and describe the implementation, testing, and validation of all the algorithms. © 2024 IEEE.

关键词： smart contract

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Clock synchronization Protocols and Models for Wireless sensor Networks 16

Clock Synchronization Protocols and Models for Wireless Sens...

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16th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Geetha, s. Latha, P. vardhini, A Raajya suganya, R. Nidhya, M.s. V.S.B Engineering College Bangalore India School of Computer Applications Dayananda Sagar University Bangalore India

ISBN: (纸本)9798331505264

Clock synchronization is a critical aspect in the operation of Wireless sensor Networks (WsNs), ensuring that sensor nodes maintain accurate time for coordinated communication and data processing. various clock synchronization algorithms have been developed to address the synchronization challenges in WsNs, aiming to align the clocks of distributed nodes efficiently. These algorithms play a crucial role in achieving synchronization by compensating for clock drift, which can significantly impact the accuracy of timekeeping among sensor nodes. Timing constraints are fundamental in WsNs, as they influence network performance and data transmission reliability. Addressing timing constraints is essential for optimizing network operations and ensuring timely data delivery. In this paper we analysed various synchronization protocols, Algorithm and techniques. Finally, we compared features of TPsN and Rbs protocols, based on accuracy, robustness TPsN is best one. © 2024 IEEE.

关键词： sensor nodes

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safeguarding Online Interaction : Utilizing Machine Learning for Detection of Malicious Intent 2

Safeguarding Online Interaction : Utilizing Machine Learning...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Kamali, s. Jeeva, v. bharathKumar, s. Harish, R. Manoj, M. V.S.B. Engineering College Department of Computer Science and Engineering India

ISBN: (纸本)9798350368109

social media platforms are facing a significant challenge with cyberbullying, which is inflicting severe mental health consequences on individuals. To help tackle this, our project is focused on creating computer programs that can identify and prevent cyberbullying on Twitter. We are going to compare three different computer methods: support vector Machine (svM), Naive bayes, and bidirectional Long short-Term Memory (bi-LsTM) models. We will assess the effectiveness of their performance by utilizing key metrics such as accuracy, precision, and recall. Our main goal is to see if these methods can detect cyberbullying early on. Additionally, we will explore the utilization of Natural Language Processing (NLP) to find threats, hate speech, and other harmful words on social media. On the whole, our project wants to highlight how beneficial computer programs can be in stopping cyberbullying and making social media a safer and more welcoming space for everyone. © 2024 IEEE.

关键词： Adversarial machine learning

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An Enhanced Approaches for Interaction Design GIs with virtual Reality 4

An Enhanced Approaches for Interaction Design GIS with Virtu...

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4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： saranya, R. Archana, M. Deebhika sree, P. Akshaya, M. Darsiniga, M.G. V.S.B. Engineering College Computer Science and Engineering Karur India

ISBN: (数字)9798350364729

ISBN: (纸本)9798350364729

In this paper, I advance the evolution of three-dimensional Geographic Information systems (GIss) and advocate for their expansion into virtual reality (vR). I commence by scrutinizing existing GIs components pertinent to three-dimensional representation: two-dimensional portrayal, digital elevation modeling, and visualization methods. subsequently, I contend that contemporary advancements in multimedia, three-dimensional modelling, and vR have matured sufficiently to be integrated into GIs frameworks. However, to realize this integration, a genuine three-dimensional GIs necessitates the following functionalities: authentic depiction of the third dimension in data and visualization, unrestricted user mobility within the three-dimensional realm, and compatibility with conventional GIs applications spanning various disciplines such as geography, geology, environmental science, engineering, and computer science. Additionally, remote sensing, employed for purposes like agricultural monitoring, environmental assessment, and urban mapping, must be adapted to operate within the three-dimensional data space, alongside v.s.bility functionalities like line-of-sight assessments. These propositions are exemplified through multiple demonstrations leveraging state-of-the-art high-memory workstations enriched with specialized engineering lexicon. © 2024 IEEE.

关键词： visualization

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An Integrated XGbRF Framework for Early Identification of Parkinson's Disease 2

An Integrated XGBRF Framework for Early Identification of Pa...

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2nd IEEE International Conference on Emerging Research in Computational science, ICERCs 2024

作者： Divya, s.v. venkadesh, P. Joan Pavithra, R. Amal, M.R. Lakshayaa, G. Logasundari, A. V.S.B College of Engineering Department of CSE Coimbatore India V.S.B College of Engineering Department of AI&DS Coimbatore India NPR College of Engineering and Technology Department of CSE Dindigul India Department of CSE Kottayyam India

ISBN: (纸本)9798331534950

Parkinson's Disease (PD) is a neurodegenerative disorder that affects movement, balance and coordination. It is a chronic disease that results from the degeneration of dopamine producing neurons in the brain. several artificial intelligence and machine learning techniques has been introduced for the early detection of PD. Early detection of PD is indispensable for slowing down its progress and providing the possibility to access the therapy. Therefore, the research focus on developing a hybrid framework (XGbRF) utilizing XGboost and random forests to enhance the accuracy of predicting the PD is proposed. It is hypothesized that the proposed framework will benefit from this complementary characteristic by using RF's strength in variance reduction through bagging and XGboost on bias minimization through boosting. This research was tested on publicly available datasets using cross-validation with hyper-parameter tuning for the optimization of optimal performance. In comparison, the proposed framework results in higher accuracy rate of 0.97, precision of 0.92, F1 score of 0.96 and AUC-ROC value of 0.93 than the existing classifiers. Therefore, the outcome of this research would essentially mean that the proposed framework may constitute a solid framework for medical diagnostics and serve as a better prognosis of PD. © 2024 IEEE.

关键词： Neurodegenerative diseases

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smart Farm Management Using Machine Learning 2

Smart Farm Management Using Machine Learning

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Prabakaran, s. Dharun, T. Gowsik, H. Anu Prakash, K. Kirubakaran, K. V.S.B. Engineering College Department of Computer Science and Engineering India

ISBN: (纸本)9798350368109

This article describes the integration of machine learning (ML) with smart agriculture management to improve agriculture through data-driven insights and automation. Machine learning algorithms analyze data from a variety of sources, including sensors and drones, providing farmers with recommendations on crop management, resource allocation and pesticides. Tracking learning helps crop classification and disease detection, while learning from tracking predicts yield and finds anomalies. Reinforcement learning makes robotic farming possible. The challenges include data quality, security and integration, but the benefits are huge;increased usage, decreased resource usage, and increased revenue. © 2024 IEEE.

关键词： smart agriculture

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Tramline surveil system Escorting Liability Observation and Localization 2

Tramline Surveil System Escorting Liability Observation and ...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： bhavadharani, K. Dheepa, M. Dharshini, M. bangadharshini, D. Dhivyabharathi, N. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

Our robotic system, which combines IoT monitoring and Arduino- based technology to detect obstacles and cracks, is important for railway track inspection. The robot's sensors are designed to match the characteristics of train tracks, ensuring accurate track defect detection and reliable obstacle recognition. This innovative approach provides an automated, low-cost solution for spotting potential hazards, with the purpose of increasing railway track maintenance efficiency. by seamlessly integrating the robot's real-time data collecting into the IoT platform, railway officials will be able to remotely monitor track conditions and perform maintenance measures as needed. Our effort addresses critical safety and maintenance challenges to create a more dependable and safer rail network by combining cutting-edge technology with railway infrastructure requirements. by offering an autonomous, low-cost, and highly sophisticated design that enhances the security and effectiveness of railroad foundation perpetuation, this innovative electronics seeks to transform railroad path inspection procedures. We hope to modernise train networks and provide a reliable, secure way of transport with the aid of this initiative. © 2024 IEEE.

关键词： Liquid crystal displays

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Eye Detection Wheelchair with smart Monitoring Using Deeplearning in CNN 2

Eye Detection Wheelchair with Smart Monitoring Using Deeplea...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Muthuchelvan, R. Divagarvasu, P. Gopinath, s. Gokul Prasanth, v. Gowtham, J. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

Individuals with severe cervical spinal cord injuries often face important challenges in interacting with their environment, including difficulties using smart phones or operating powered wheel chairs. For those with tetraplegia, Eye-tracking technologies have emerged as a crucial tool for enhancing control and convey. However, confinement in accuracy, practicality, an calibration time often plague conventional eye-tracking devices. Researchers have explored Convolutional Neural Networks(CNNs) as a potential solution to address these shortcoming in AI-powered eye tracking system. CNNs a type of deep learning architecture excel at recognizing complex pattern in a data, leading to more precise and reliable eye tracking. An mostly good way to argument the eye tracking correctness method. This technique outline a more reliable and result way to interact with digital mechanism by using deep learning algorithms to admit and track eye movements based on blink count. This technology has the power to conversion the way we interact with digital technologies, greatly improving their usefulness and accessibility for those who suffer from confusion or impairments. For human beings who have trouble with standard eye tracking because of motor restrictions, vision depletion, or other reductions © 2024 IEEE.

关键词： Convolutional neural networks

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Data security in Communication using blockchain and Key based Protocols 2

Data Security in Communication using Blockchain and Key Base...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Prabakaran, s. Harinivaash, K. Prasad, R. Kaviyan, J. Rabin, D. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

The development of global communication networks depends on satellite communication. Due to its lower stability and reach, satellite communication networks have garnered a lot of attention recently as a means of reducing the limitations of terrestrial networks. Numerous inconveniences exist, including inadequate storage space, security, and data processing capacity. Illegal entry turned out to be the difficult one. satellite physical limitations in terms of available power and area result in limited data processing capability, storage and security limitations, and the data may be exposed to alteration or contamination by intruders. since satellite communication has become more crucial in the development of global communication networks, there have been worries regarding its security. This project proposes to use the QKD protocol, which relies on identification and privacy protection, along with blockchain technology to create A network of satellite communication. To accomplish this, an architecture that consists of conventional and constrained devices connected to the blockchain via a wireless heterogeneous network has been developed. The communication is conducted by registration, authentication, and revocation. After receiving the data from the satellite, the terrestrial base station will log all important parameters on the distributed blockchain and remove any certificates belonging to rogue nodes. The proposed Chain and QKD system, which is based on satellites, offers a high degree of security for rapidly growing applications such as self-driving cars, future 6G and larger networks, and the Internet of Things. © 2024 IEEE.

关键词： satellite communication systems

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