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Sign Language Translation Across Multiple Languages 4

Sign Language Translation Across Multiple Languages

引用

4th International Conference on Emerging Systems and Intelligent Computing, ESIC 2024

作者： Antad, Sonali M. Chakrabarty, Siddhartha Bhat, Sneha Bisen, Somrath Jain, Sneha Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350349856

Sign Language serves as the only mode of communication for people who are speech and hearing disabled. Despite this, they face many difficulties in communication due to different sign languages across the world using different signs and symbols. This project aims to bridge this gap and make communication easy and accessible for all. Through the utilization of Convolutional Neural Networks (CNN) and other deep learning algorithms, the project provides a platform to people to choose between Indian Sign Language and American Sign Language and further provides translation to multiple Indian regional languages to improve communication between people. This serves a two-way purpose by enabling people who are trained in different sign languages to communicate efficiently as well as providing written text in multiple languages for people who cannot interpret sign language and are proficient only in regional languages. This comprehensive strategy strives to eliminate communication barriers, contributing to a more equitable society. This innovative project has the potential to significantly enhance communication inclusivity and accessibility for the global deaf and hard of hearing community. © 2024 IEEE.

关键词： Audition

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Block Verify: Generation and Validation of e-Certificate Using Blockchain 2

Block Verify: Generation and Validation of e-Certificate Usi...

引用

2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Jadhav, Swati Jadhav, Daksh Jadhav, Shivendra Shelke, Jiva Kakade, Dheeraj Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798331519056

BlockVerify is a decentralized platform created to offer a safe and impenetrable way to use blockchain technology for document verification. BlockVerify guarantees the authenticity of documents by utilizing the immutability and transparency of the Ethereum blockchain. This makes it the perfect solution for individuals and organizations that need strong document verification. Users of BlockVerify can upload metadata for decentralized storage, including IPFS hashes, along with document hashes. The platform makes sure that the only people who can add and edit document records are authorized exporters who are managed and added by the contract owner. Document verification, ownership transfer, exporter management, and hash storage are important aspects. The project develops smart contracts using Solidity and Ethereum (Sepolia testnet), and it has an easy-to-use online interface using technologies like HTML, CSS and JavaScript to promote communication and MetaMask for secure wallet interactions. With future ambitions to expand to the mainnet and support new document kinds, BlockVerify intends to combat document fraud by offering a dependable way to check the legitimacy of documents. © 2024 IEEE.

关键词： Smart contract

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Image Based Plant Disease Detection using CNN: An Experimental Research 15

Image Based Plant Disease Detection using CNN: An Experiment...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Wankhede, Disha Narnaware, Aman Baral, Abhaykumar Gawade, Akash Valsange, Atharva Department of Computer Engineering Vishwakarma Institute of Information Technology India

ISBN: (纸本)9798331300579

The first step in preventing losses in agricultural product output and quantity is the identification of plant diseases. The study of patterns that are visible to the human eye on plants is referred to as plant disease research. Plant disease identification and health monitoring are essential for sustainable agriculture. Manually keeping an eye on plant diseases is really challenging. It necessitates an enormous amount of processing time, a great deal of labor, and knowledge of plant diseases. Therefore, plant disease detection uses image processing. A number of processes are involved in disease detection, including feature extraction, classification, segmentation, pre-processing, and image acquisition. This study examined techniques for identifying plant illnesses using photos of their leaves. A few segmentation and feature extraction techniques for plant disease identification were also covered in this work. © Grenze Scientific Society, 2024.

关键词： CNN Architecture Convolution Neural Network Deep learning Plant disease detection

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Team IndiDataMiner at IndoNLP 2025: Hindi Back Transliteration - Roman to Devanagari using LLaMa 1

Team IndiDataMiner at IndoNLP 2025: Hindi Back Transliterati...

引用

1st Workshop on Natural Language Processing for Indo-Aryan and Dravidian Languages, IndoNLP 2025

作者： Kumar, Saurabh Kakadiya, Dhruvkumar Babubhai Singh, Sanasam Ranbir Department of Computer Science and Engineering Indian Institute of Technology Guwahati India

ISBN: (纸本)9798891762145

The increasing use of Romanized typing for Indo-Aryan languages on social media poses challenges due to its lack of standardization and loss of linguistic richness. To address this, we propose a sentence-level back-transliteration approach using the LLaMa 3.1 model for Hindi. Leveraging fine-tuning with the Dakshina dataset, our approach effectively resolves ambiguities in Romanized Hindi text, offering a robust solution for converting it into the native Devanagari script. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Analysis of the various YOLOv8 models in Detecting Defects in PCB 15

Analysis of the various YOLOv8 models in Detecting Defects i...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Raj, Abhishek Ahlawat, Priyanka National Institute of Technology Department of Computer Engineering Kurukshetra India

ISBN: (纸本)9798350370249

In the arena of electronics, the Printed Circuit Board (PCB) forms the cornerstone of every component, extending from everyday gadgets to advanced defense equipment. The escalating pace of modern life necessitates accelerated PCB production, calling for swift and precise mechanisms to ensure defect-free output for reliable manufacturing. Though such quality control tasks were traditionally manual, the advent of machine learning and deep learning has ensured automated and reliable solutions. A standout among these is YOLO, a speedy computer vision algorithm renowned for its unmatched speed and accuracy. This paper seeks to conduct an all-encompassing study of the cutting-edge YOLOv8 sub-models, delving into their individual performance attributes. The work encapsulates the implementation of these YOLOv8 models, followed by a rigorous analysis of their results on a range of metrics like mAP50, mAP50 - 95, precision, and recall. An integral part of this study is the preprocessing of the HRIPCB dataset, comprising six distinct defect categories, namely Missing hole, Mouse bite, Spur, Spurious copper, Open circuit, and Short. The ensuing robust methodology involves comprehensive data preprocessing, data cleansing, and standardization. Ensuring a high-level of data quality, image enhancement techniques such as Colour Balance Adjustment, Histogram Equalization, and Image Filtering - Sharpening are employed. The study shines a spotlight on the individual training and testing processes of the YOLOv8 sub-models, namely v8n, v8s, v8m, v8l, and v8x, leveraging various hyperparameters to optimize model performance. By surpassing the 95.8% mAP50 achieved by earlier YOLO versions, this research aspires to revolutionize PCB defect detection. It paves the way for enhanced quality control mechanisms in PCB manufacturing, thus contributing to the advancement of electronics production regimes © 2024 IEEE.

关键词： Deep Learning Defect detection Image recognition Printed circuit board YOLOv8

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Online News: Event Detection and Community Identification 8th

Online News: Event Detection and Community Identification

引用

8th International Conference on Information and Communication technology for Intelligent Systems, ICTIS 2024

作者： Kulkarni, Radhika V. Suryawanshi, Snehal Shirsath, Aditya Sonone, Swati Phapale, Siddhi Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9789819766833

Nowadays, reading online news is very common among people. The amount of information on the web is growing at a rapid pace, which is driving up the consumption of online news. As a result, a system to gather and disseminate significant real-world events from massive amounts of web data is now required. In addition, a lot of businesses rely their judgements on global events that happen every day. One of the most important tasks is event recognition, which is finding news articles about the same occurrence and grouping them together. This method improves user navigation and gives news pieces a conceptual structure. To group linked news documents, it makes use of TF-IDF analysis, time-series analysis, and community detection. For interactive investigation and analysis, the system interfaces with an easy-to-use website that offers sentiment analysis and 3D visualizations for improved interpretability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Community detection Event detection News stream

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Evaluating CUDA-Aware Approximate Computing Techniques 3

Evaluating CUDA-Aware Approximate Computing Techniques

引用

3rd International Workshop on Resource AWareness of Systems and Society, RAW 2024

作者： Öz, Işıl Computer Engineering Department Izmir Institute of Technology Izmir Turkey

Approximate computing techniques offer performance improvements by performing inexact computations. Moreover, CUDA programs written to be executed on GPU devices employ specific features to utilize the parallel computation units of heterogeneous GPU architectures. While generic software-level approximate computing techniques have been applied to heterogeneous CUDA programs, CUDA-specific approaches may introduce promising performance improvements by not corrupting the target computations. In this work, we propose software approximation techniques for CUDA programs: kernel-aware loop perforation, partition-level synchronization, block-level atomic operations, and warp divergence elimination. We perform source code transformations on target benchmark programs by applying our techniques. We evaluate performance improvements by trading off accuracy in our target computations. Our experimental results reveal that CUDA-aware approximation techniques offer significant performance improvements at the expense of acceptable accuracy loss. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Graphics processing unit

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Ethereum-Based Decentralized Crowdfunding Platform 6th

Ethereum-Based Decentralized Crowdfunding Platform

引用

6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Jadhav, Swati Patil, Rohit Patil, Saee Patil, Shweta Patil, Varun Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9789819940707

Crowdfunding refers to investments of people in some projects and businesses. Sometimes, it also refers to donations from people for societal goodness. Many online platforms are available that support crowdfunding for different purposes. But most of the time investors or donors have a kind of doubt about whether their money is being utilized for the right purpose or not. The platforms are centralized;once the organization receives the donation, donors have no idea about the further transactions which the organization does. Many times, crowdfunding campaigns are not monitored and some of them have proven to be bogus. Due to such issues, projects have been extensively delayed in their completion. So, crowdfunding platforms are one area in which blockchain technologies can be used. Blockchain has been used in many different sectors to increase transparency among the users and people involved in the system. Blockchain is predicted to be used by the majority of technology as an effective method of conducting transactions online in the future. By integrating Ethereum-based contracts into the crowdfunding campaign, this project aims to overcome these problems, allowing the contracts to be fully automated, preventing fraud, and ensuring that projects are completed within the specified timeframe. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Smart contract

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Bettercall: AI based legal assistant 5

Bettercall: AI based legal assistant

引用

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

作者： Dhore, Manikrao Vimal, Aryan Agrawal, Avish Bajaj, Raghav Barde, Rohan Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350367171

This research introduces an AI-based chat-bot designed to enhance access to legal and judicial information in India. The system leverages advanced natural language processing techniques to transform legal texts into vector embeddings, facilitating semantic search capabilities that improve the user experience in retrieving relevant legal information. The chat-bot aims to provide primary legal aid, support informed decision-making, offer instant access to legal rights and information, and promote legal awareness among users. The methodology includes rigorous data collection, cleaning, and pre-processing processes to ensure high accuracy and reliability. The research also navigates to a potential implementation of the solution and addresses the complexities, results and challenges faced by the authors. The research highlights the novelty of the approach and addresses existing gaps in scalability, multilingual support, and domain coverage, presenting a comprehensive system ready for real-world deployment. © 2024 IEEE.

关键词： Embeddings

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Forecasting Renewable Energy Generation: A Predictive Modelling Approach 2

Forecasting Renewable Energy Generation: A Predictive Modell...

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2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Mondal, Priotosh Bhatia, Aditi Panjwani, Roshini Dokare, Indu Ves Institute of Technology Department of Computer Engineering Mumbai India

ISBN: (纸本)9798350368413

India's rapid urbanization demands innovative solutions to address energy consumption patterns while reducing reliance on fossil fuels. This research paper explores the application of predictive modelling techniques like Multilayer Perceptron and Polynomial Regression to forecast solar energy generation and Long Short-Term Memory (LSTM) models to forecast wind energy generation, thereby facilitating efficient energy planning in major Indian cities. The proposed system aims to create a web-based platform that integrates these predictive models to display real-time temperature conditions and the corresponding amount of energy that solar and wind sources can provide in specific locations, thus promoting smart cities and smart homes. By utilizing the website, energy planners will be able to compare the generated energy from wind and solar sources, enabling informed decisions on which resource best meets the energy requirements of housing settlements. © 2024 IEEE.

关键词： Wind forecasting

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