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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Jayaswal, Bharat Ghosh, Soumya K. Indian Institute of Technology Department of Computer Science and Engineering Kharagpur India

ISBN: (纸本)9798331531195

Maritime Intelligence is essential for safeguarding maritime interests of coastal nations. Traditionally, vessel movements are tracked using self-reported positions via Automatic Identification System (AIS) transponders. However, vessels engaged in illicit activities often disable their AIS transponders to evade detection, thereby going dark. Satellite-based sensors, such as Synthetic Aperture Radar (SAR) and Visible Infrared Imaging Radiometer Suite (VIIRS) can be used to detect Dark Vessels. However, extraction of actionable insights for maritime intelligence on Dark Vessels is posed with several challenges. The spatial estimation of activities of vessels over various time periods is complicated due to spatial and temporal overlaps in satellite scans. This poster presents our ideas on knowledge discovery framework that integrates spatial analytics methods to gain actionable insights on Dark Vessels. Preliminary results are shown on Global Fishing Watch (GFW) Dataset of Dark Vessels. © 2025 IEEE.

关键词： Radar imaging

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A Comprehensive Analysis of Dithering Algorithms and GPU Implementations 3

A Comprehensive Analysis of Dithering Algorithms and GPU Imp...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Kulkarni, Radhika V. Deshpande, Aaditya Dagale, Pratik Manmode, Devyani Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350375190

This research paper conducts a thorough comparative analysis of various dithering algorithms, prioritizing the GPU-optimized Floyd-Steinberg algorithm. Dithering plays a crucial role in improving image quality in constrained display scenarios. The study evaluates popular algorithms, including Bayer matrix, Ordered dithering, and Error Diffusion, while specifically exploring enhancements in the Floyd-Steinberg algorithm through GPU optimization. Quantitative metrics such as MSE, PSNR, and SSI are employed, alongside subjective assessments, to gauge algorithmic performance. The research delves into adaptability across color spaces and image types, providing insights for algorithm selection. Emphasizing real-time applications, the study offers developers valuable guidance in choosing efficient dithering techniques. The GPU-optimized Floyd-Steinberg algorithm emerges as a promising solution, showcasing its potential for accelerated computing environments and resource-intensive tasks. © 2024 IEEE.

关键词： Graphics processing unit

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Image Forensics—Analysis of Manipulated Images 4th

Image Forensics—Analysis of Manipulated Images

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4th International Conference on Innovations in Computational Intelligence and computer Vision, ICICV 2024

作者： Mamidwar, Aryan Mugalikar, Atharva Ghuge, Vivek Godse, Divija Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9789819769940

With the emergence of low-cost internet connections, there has been significant growth in internet usage, and people are using social media to a larger extent. Social media forms a major part in human-to-human communication in the twenty-first century. Enormous number of images are shared and circulated on the social media platforms. Tampering and editing of the images are done even though internet and social media platforms like Facebook, Instagram, and Twitter connect people all over the world;evils in a society corrupt them. Small errors in information or manipulated images can wreak havoc and have unintended repercussions. Altered photos are a major source of misinformation/fake news and are frequently used maliciously, such as for mob provocation. Cases of similar incidents have grown during the previous decade. So, there should be one system which will filter this manipulated image before it leads to some major destruction. In the system mentioned in this paper, use of Error Level Analysis has been employed along with Convoluted Neural Network (CNN). The motive of this research work is to develop a system that will detect the manipulated image and verify its authenticity. By utilizing the machine learning algorithm ELA to detect changed photographs, the research helps reduce the dangers that edited images pose to society by keeping an eye on them. With a 98.5% accuracy rate, the Xception CNN model presented in this study performs well on the dataset. The dataset used is CASIA II, and it contains a total of 12,323 images and is furthermore divided into subsets. These folders consist of 7200 authentic images and 5123 tampered images. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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Building a Compassionate GenAI-integrated ASL Translator for YouTube Video 4

Building a Compassionate GenAI-integrated ASL Translator for...

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4th IEEE Asian Conference on Innovation in technology, ASIANCON 2024

作者： Uke, Shailaja Godse, Shreyas Giramkar, Anshuman Gupta, Snehal Indulkar, Pooja Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350354218

Video streaming is crucial for modern entertainment, education, and communication, providing accessible content to a wide audience globally. However, deaf and hard of hearing communities may face barriers due to lack of or inadequate closed captioning, hindering their ability to fully engage with and comprehend streamed content. Our paper navigates through a transformative project centered on the development of a Generative AI for YouTube video translation, integrating Google Cloud with a compassionate approach to enhance accessibility for the Deaf and Hard of Hearing community through American Sign Language (ASL) translations. Leveraging cutting-edge technologies such as Google Cloud's Gen-AI and the Palm 2.0 Text Bison model, the project aims to revolutionize the landscape of YouTube video content by providing ASL translations for a more inclusive user experience. Key objectives include the creation of an ASL Translation Tool for YouTube videos, emphasizing inclusivity beyond mere translation to engage ASL users effectively. By harnessing Google Cloud technologies and APIs in a seamless and compassionate manner, the project ensures a thoughtful code structure and organized outputs that reflect its commitment to fostering inclusivity, understanding, and accessibility for all, particularly for the ASL community. Through this endeavor, the project endeavors to showcase how technology, when employed with empathy and foresight, can serve as a catalyst for positive change in promoting inclusivity and accessibility for diverse communication needs. © 2024 IEEE.

关键词： Video streaming

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Real-time Air Quality Monitoring and Context-aware Alert System 17

Real-time Air Quality Monitoring and Context-aware Alert Sys...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Kakde, Anuj Pagoti, Yashwant Krishna Nikumbh, Sarthak Karmakar, Prasenjit Chakraborty, Sandip Indian Institute of Technology Department of Computer Science and Engineering Kharagpur India

ISBN: (纸本)9798331531195

Air quality monitoring is gaining increasing importance as awareness about the health impacts of air pollution continues to grow. These monitors typically track air pollutants to give users a clearer picture of their environment. Accurate and real-time monitoring increases our understanding of the surrounding air we breathe and allows us to improve it. The proposed system helps users minimize their exposure to harmful pollutants by providing real-time data on the concentration of various gases. The system triggers alerts directly to the subscribed user's mobile phones in case of any hazardous situations so that the user can take appropriate actions immediately to resolve the issue. Our extensive data collection and evaluation with off-the-shelf machine learning models indicated an overall F1-score of 99.54 (±0.5)% with a simple random forest model in classifying burning, cooking, occupancy in a closed room, using aerosol products, based on the sensor's readings. © 2025 IEEE.

关键词： Indoor air pollution

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Multimodal emotion recognition model via hybrid model with improved feature level fusion on facial and EEG feature set

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Multimedia Tools and Applications 2025年第1期84卷 1-36页

作者： Singh, Pratima Tripathi, Mukesh Kumar Patil, Mithun B. Shivendra Neelakantappa, Madugundu Department of Computer Science and Engineering Galgotias University Gautam Buddh Nagar Uttar Pradesh India Department of Computer Science and Engineering Vardhaman College of Engineering Telangana Hyderabad India Department of Computer Science and Engineering N K Orchid College of Engineering & Technology Maharastra Solapur India Department of Computer Application D. K. College Dumraon Bihar Buxar India Department of Information Technology Vasavi College of Engineering Telangana Hyderabad India

In recent years, academics have placed a high value on multi-modal emotion identification, as well as extensive research has been conducted in the areas of video, text, voice, and physical signal emotion detection. This paper proposes a novel multimodal emotion recognition model that employs a hybrid model with AMIG-based feature fusion on facial and EEG feature sets. The EEG signal and facial image are subjected to preprocessing to remove unwanted background noises with the Butterworth filter and Viola Jones Algorithm, respectively. While considering the pre-processed EEG signal, features such as EWFS-transform, wavelet features, and CSP-based features are extracted. In the proposed EWFS-transform, the window function is modified by using the frequency function and updated STFT. Conversely, the features including SE-AMM-EST-based features;LGXP and GLCM are extracted while considering the preprocessed face image. In the proposed SE-AMM-EST-based features, the mean of shape is updated and covariance in PCA for extracting texture-based features. In order to extract redundant free essential features, AMIG-based feature fusion is proposed. Further, the fused features are fed into a proposed hybrid model that includes LSTM and AML-CNN models. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Textures

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Decentralized Music Platform: A Blockchain-based Solution for NFT Music Distribution and Royalty Management 5

Decentralized Music Platform: A Blockchain-based Solution fo...

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5th International Conference on Image Processing and Capsule Networks, ICIPCN 2024

作者： Dhore, M.L. Kate, Sumedh Khandelwal, Dipkul Khandetod, Arya Kharade, Aishwarya Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350367171

Blockchain technology, which rests on impermeable, decentralized ledgers, has found use in a variety of fields beyond its original connection to cryptocurrencies. Its ability to create safe, readable, and unchangeable records is its core strength. The proposed research work presents a novel approach to music distribution that makes use of blockchain technology to enable artists to sell their work directly to customers, doing away with middlemen. To provide secure and transparent transactions, the system uses a decentralized ledger to record and authenticate music transactions. Automated royalty distribution made possible by smart contracts ensures that artists receive just pay. Musicians have more control over their creative property and income by eschewing conventional middlemen. Additionally, the platform incorporates an easy-to-use interface that allows artists to upload, manage, and monetize from their works with ease. This creative strategy reduces concerns of money leakage and piracy while promoting direct relationships between musicians and fans, resulting in a more egalitarian music market. © 2024 IEEE.

关键词： Smart contract

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SlidEar: Exploring eSense in-Ear Wearable for Voice-Assisted Smart Slide Supervision 17

SlidEar: Exploring eSense in-Ear Wearable for Voice-Assisted...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Mondal, Susmita Zingre, Sameeran Ravishankar Chakraborty, Suchetana Indian Institute of Technology Department of Computer Science and Engineering Jodhpur India

ISBN: (纸本)9798331531195

In corporate settings, conferences, or classrooms, an orator relies on manual slide transitions, which can disrupt their presentation flow. Presentation devices can be inaccessible due to the physical limitations of individuals, reducing engagement with the audience. Traditionally used remote-controlled wireless presenters are hand-held devices that usually require a compatible connector slot for the presentation device and partially engage one hand of the orator. To ease the hand-free presentation of slides, we introduce SlidEar, a voice-assisted smart slide supervision successfully tested on eSense in-ear wearables. SlidEar leverages voice recognition fusion with wearable sensors to facilitate seamless slide operations. It allows real-time feedback on natural language commands during the presentation of slides. Compared with conventional methods, SlidEar enhances engagement and accessibility through hand-free in-ear placement and helps the orator focus on delivering their content without any disruption or distraction. The evaluation shows promising results that improve the presentation experience profusion. SlidEar significantly reduces errors and can be widely adopted in diverse presentation scenarios. © 2025 IEEE.

关键词： Speech recognition

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Vision Voice: A Raspberry Pi-Based Text-to-Audio Converter for the Visually Impaired

Vision Voice: A Raspberry Pi-Based Text-to-Audio Converter f...

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2024 International Conference on Emerging Innovations and Advanced Computing, INNOCOMP 2024

作者： Thopate, Kaushalya Amrutkar, Kavya Kasliwal, Tarun Karvir, Shaunak Kumbhar, Omkar Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350376470

Vision Voice is an innovative assistive technology project. This project aims to improve the accessibility and quality of life of visually impaired people. It utilizes Raspberry Pi 3 as its core hardware platform and runs on a Python-based code framework. Vision Voice's main goal is to empower the visually impaired by offering smooth text-to-audio conversion technology. It offers an effortless solution for the visually impaired to access and interact with digital content. Users can enter text, which will then be converted to crisp and natural audio output. This breakthrough technology enables blind individuals to access a wide range of resources including digital resources, educational materials, literature, and news. It gives them a sense of empowerment and independence. By focusing on accessibility and user empowerment, Vision Voice embodies the future of assistive technology, bridging the digital divide and ensuring that the visually impaired can fully participate in the digital age. © 2024 IEEE.

关键词： Assistive technology

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A Scalable and Fault-Tolerant 5G Core on Kubernetes 17

A Scalable and Fault-Tolerant 5G Core on Kubernetes

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Paul, Sourav Keluskar, Tanvi Vutukuru, Mythili Indian Institute of Technology Department of Computer Science and Engineering Bombay India

ISBN: (纸本)9798331531195

The 5G core is an important part of a 5G network, and with the exponential growth of connected devices and dynamic traffic conditions, it is essential for the 5G core to be scalable and fault-tolerant. This requirement is even more important with the softwarization of the packet core and cloud-based deployments. This paper presents a comparison of design choices when building a scalable and fault-tolerant 5G core on a Kubernetes-orchestrated cloud platform. Prior work in this direction does not fully explore all design choices, or is not compliant with 3GPP standards. In contrast, we start with a 3GPP-compliant production-grade 5G core, and build multiple variants of cloud-native 5G core components. We leverage Kubernetes' automatic failover, and auto-scaling capabilities in different ways to make the 5G core scalable and fault-tolerant. We conduct extensive experiments to evaluate the scalability and resilience of various design choices, and to quantify the overheads of cloud deployments. Our work exposes tradeoffs between performance and fault tolerance, and provides insights on how best to design a scalable and fault-tolerant 5G core on Kubernetes. © 2025 IEEE.

关键词： Cloud platforms

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