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A Comparative Study of Deep Image Retrieval Models Leveraging Deep Features

A Comparative Study of Deep Image Retrieval Models Leveragin...

引用

2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Jain, Ashish Varshney, Sudeep SET Sharda University Dept. of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350378092

This review investigates how deep learning methods can be utilized for efficient image retrieval based on content. Obtaining accurate images from vast digital collections poses significant challenges, motivating research in CBIR. The effectiveness of these methods varies depending on the dataset's type and size, with certain algorithms excelling with specific dataset characteristics. An extensive and well-structured review of successful image retrieval techniques is given in this paper. Our primary objective is to evaluate various deep learning models applied by researchers and compare their performance based on the outcome of evaluation matrices. These models encompass CNNs, DBNs, and other deep architectures tailored for image retrieval tasks. By synthesizing insights from this review, researchers can make informed decisions regarding model selection and potentially enhance retrieval performance by leveraging advanced deep learning features. The importance of deep features in image retrieval is the ability to capture complex visual patterns and semantic information that cannot be easily extracted by traditional handcrafted features. With the increasing volume of online images, Image retrieval using deep learning has become crucial for applications like object recognition, image retrieval, and image search engines. © 2024 IEEE.

关键词： Contrastive Learning

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A Comparative Analysis of Early Departure Buttons in Coordinated Control of EV Charging

A Comparative Analysis of Early Departure Buttons in Coordin...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Ozceylan, Baver Hoogsteen, Gerwin Hurink, Johann L. University of Twente Dept. of Electrical Engineering Mathematics and Computer Science Enschede Netherlands

ISBN: (纸本)9789531842976

The increasing adoption of electric vehicles (EVs) necessitates the efficient management of large EV parking facilities to prevent them from exceeding grid capacity and to improve the overall user experience. This paper introduces a data-driven approach for coordinated control of EV charging in an office parking facility, integrating Early Departure Buttons (EDB) into the system. These buttons provide a binary option for users to indicate an earlier departure than a predefined time. We employ the EDB data to improve departure time estimations and to address issues where EVs receive no or only very low energy. We utilize three datasets originating from different geographical locations. One dataset displays a user pattern where users leave shortly after completing their charging, unlike the other datasets which follow typical working hours. Our simulations show that the unique user pattern significantly increases fairness among users, and integrating EDBs improves fairness for the other datasets to levels similar to those of quick station turnover. © 2024 IEEE.

关键词： electric vehicle energy management smart grid user information

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Developing a Low-Cost Prosthetic Hand with Real-Time Machine Learning Capabilities 23

Developing a Low-Cost Prosthetic Hand with Real-Time Machine...

引用

8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Adani, M. Syakhisk Naufal Widasari, Edita Rosana Setiawan, Eko Dept. Computer Engineering Faculty of Computer Science Brawijaya University Indonesia

ISBN: (纸本)9798400708503

The global prevalence of arm amputations, particularly transradial or below-elbow amputations, presents a pressing challenge due to the high costs of commercially available prosthetic hands. This issue is particularly acute in developing countries, where financial constraints hinder access to functional prosthetic solutions. Addressing this gap, this research introduces an innovative approach that merges electromyography (EMG) signal recognition and machine learning to develop an affordable and versatile bionic below-elbow prosthetic hand. The integration of EMG signals for control, coupled with machine learning algorithms, enables accurate classification of hand movements, resulting in enhanced movement precision and a broader range of gestures. This solution overcomes limitations in existing prosthetic hands, offering advanced EMG-based control and comprehensive movement capabilities, empowering users to perform intricate tasks and regain functional autonomy. The study undertakes a comprehensive analysis of the developed system's performance, encompassing hardware, software, and machine learning components. Results show promising accuracy levels for movement classification using the K-Nearest Neighbors (KNN) machine learning method. Execution time variations are observed among subjects and gestures, influenced by factors such as subject sensitivity and gesture complexity. Energy consumption analysis reveals disparities in power usage among different movements, emphasizing the impact of movement complexity on power requirements. A cost analysis demonstrates the affordability of the prototype, positioning it as a cost-effective alternative to existing prosthetic hand options. Comparing this solution to other research and commercial prosthetic hands highlights its uniqueness, particularly its emphasis on affordability. © 2023 Owner/Author.

关键词： Nearest neighbor search

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Deepfakes - Generating Synthetic Images, and Detecting Artificially Generated Fake Visuals Using Deep Learning 14

Deepfakes - Generating Synthetic Images, and Detecting Artif...

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14th International Conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Mishra, Ayushi Bharwaj, Aadi Yadav, Aditya Kumar Batra, Khushi Mishra, Nidhi Amity University Noida Dept. of Computer Science and Engineering Noida201313 India

ISBN: (纸本)9798350344837

The abstract delves into the groundbreaking realm of DeepFakes, a revolutionary synthesis of deep learning and synthetic media. Central to DeepFake generation is the utilization of Generative Adversarial Networks (GANs), particularly the innovative mechanisms of face reenactment involving DCGANs (Deep Convolutional GANs) and Autoencoders. These technologies empower a generator to transform random noise into hyper-realistic visuals, capturing intricate details such as facial expressions and lighting conditions through latent space interpolation. The adversarial interplay between generator and discriminator continuously refines the authenticity of the generated content. While DeepFakes unlocks creative possibilities for artists and filmmakers, the abstract underscores the ethical concerns surrounding misinformation, privacy breaches, and trust erosion in digital media. The discourse navigates the delicate balance between creative freedom and responsible use, highlighting how DeepFakes, with their roots in advanced deep learning techniques, redefine our perception of synthetic media, challenging notions of reality in our increasingly digital world. © 2024 IEEE.

关键词： Digital storage

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Blockchain-Aided Privacy Preserving Framework for Federated Learning 2

Blockchain-Aided Privacy Preserving Framework for Federated ...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Jain, Chitresha Chaudhari, Payal Pandit Deendayal Enerygy University Dept. of Computer Science and Engineering Gandhinagar India

ISBN: (纸本)9798350306415

Blockchain has shown tremendous growth in the past few years because of its decentralized and immutable architecture, which makes transactions transparent, making it a feasible choice for authentication and security purposes. Federated learning is a collaborative model training method that can benefit from Blockchain Technology. It is vulnerable to a single point of failure while performing aggregation in a centralized server architecture. Blockchain-aided Federated Learning can be proposed for enhancing the security and privacy of user data together with removing a single aggregator. It also supports a mechanism of giving rewards to users in the form of cryptocurrency to encourage users to follow the protocol. This paper introduces a framework named Blockchain-Aided privacy preserving framework for Federated Learning (BPPF) that helps in model training on the user side with added security and privacy. © 2024 IEEE.

关键词： Blockchain Differential Privacy Federated Learning Security

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'Vulnerabilities in Smart Contracts: A Detailed Survey of Detection and Mitigation Methodologies'

'Vulnerabilities in Smart Contracts: A Detailed Survey of De...

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2024 IEEE International Conference on Emerging Technologies in computer science for Interdisciplinary Applications, ICETCS 2024

作者： Kumar, Nayantara K Honnungar, Niranjan V Sharwari Prakash, M. Lohith, J.J. B.M.S. College of Engineering Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350372502

In the ever-changing world of blockchain technology, the emergence of smart contracts has completely transformed the way agreements are executed, offering the potential for automation and trust in decentralized systems. Despite their built-in security features, smart contracts still face persistent vulnerabilities, resulting in significant financial losses. While existing studies often approach smart contract security from specific angles, such as development cycles or vulnerability detection tools, this paper adopts a comprehensive, multidimensional perspective. It delves into the intricacies of smart contract security by examining vulnerability detection mechanisms and defense strategies. The exploration begins by conducting a detailed analysis of the current security challenges and issues surrounding smart contracts. It then delves into established frameworks for classifying vulnerabilities and common security flaws. The paper examines existing methods for detecting, and repairing contract vulnerabilities, evaluating their effectiveness. Additionally, it provides a comprehensive overview of the existing body of knowledge in smart contract security-related research. Through this systematic examination, the paper aims to serve as a valuable reference and provide a comprehensive understanding of the multifaceted landscape of smart contract security. © 2024 IEEE.

关键词： Smart contract

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Genetic Algorithms and Computational Biology in Crop Improvement

Genetic Algorithms and Computational Biology in Crop Improve...

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Anand, Pushpam Raj, Shreyansh Pradhan, Soumya Ranjan Shah, Syed Sajid Hussain Verma, Shreyash Kumar, Vinod Chandigarh University Bachelor of Engineering Dept. of Computer Science Punjab 140413 India

ISBN: (纸本)9798331543617

Genetic algorithms (GAs) are a subset of machine learning and can potentially solve complex biological challenges in agriculture, including crop improvement. These algorithms help simulate the process of nature selection using techniques such as Mutation, Crossover, and Selection. Integrating genetic algorithms with computational biology can help improve the agriculture field's outcomes such as crop yield, resistance to crop diseases, and crop quality, and crops are more adaptable in the environment. The role of genetic algorithms in agriculture focuses on improving breeding strategies, optimizing agricultural outputs, sustainable farming, and enhancing global food security. © 2024 IEEE.

关键词： Livestock

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Automatic Detection of Hypernasality in Cleft Palate Speech Using Phase Feature 14

Automatic Detection of Hypernasality in Cleft Palate Speech ...

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14th International Conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Hashreta, Kanuri Naga Venkata Sai Lalitha, Duggaraju Sri Lahari, Maddula Lalitha Sri, Pittala Deepthi Dubey, Akhilesh Kumar Koneru Lakshmaiah Education Foundation Dept. of Computer Science and Engineering Guntur India

ISBN: (纸本)9798350344837

The detection of hypernasality, a speech disorder common in children with cleft palate, typically involves analyzing vowels within speech stimuli. An essential acoustic cue for hypernasality detection is the presence of a nasal peak near the first formant (F1). Traditionally, a two-step process is employed, where vowel selection from stimuli is initially performed through manual annotation, followed by automatic feature extraction and classification. This work introduces a novel method for hypernasality detection, automating the entire process, including vowel region selection, feature extraction, and classification. The method leverages vowel onset points for the automatic identification of the vowel region. Subsequently, a modified group delay cepstral coefficient feature is extracted from this automatically selected vowel region. The feature is extracted from modified group delay spectrum, offering enhanced resolution to distinguish closely spaced nasal peaks and the F1, thus improving the capture of nasality evidence. The proposed method demonstrates promising results when applied to hypernasality detection using a support vector machine classifier with the accuracy of 83.50% for /a/ vowel and 93.21% for /i/ vowel. © 2024 IEEE.

关键词： Support vector machines

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Applications and Approaches of Sentiment Analysis: A Current Review 6

Applications and Approaches of Sentiment Analysis: A Current...

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6th IEEE International Conference on Recent Advances in Intelligent Computational systems, RAICS 2024

作者： Sandra, G. Silas, Salaja Rajsingh, Elijah Blessing Karunya Institute of Technology and Sciences Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350381689

Limitless amount of data is loaded in every moment in social media platforms in the forms of audio, videos, texts, and photos. They are rich sources of information, which has immense value. Hence extraction of information from them is inevitable. Many methods are employed for this and the popular among them to mine the information is sentiment analysis. To materialize the objectives of this study, a systematic review of articles published from 2013 to 2023 was done. Our study reviewed the relevance of sentiment analysis in social media by probing the different approaches followed, the platforms used and its applications, as its main objectives. Its results show that majority of studies applied machine learning approach or hybrid method for executing sentiment analysis. © 2024 IEEE.

关键词： applications approaches categories dataset sentiment analysis

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Quora Question Sincerity Detection Using BERT-Based Framework 14

Quora Question Sincerity Detection Using BERT-Based Framewor...

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14th International Conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Arora, Drishti Aggarwal, Garima Asif, Farhan Amity University Dept. of Computer Science and Engineering Uttar Pradesh Noida India

ISBN: (纸本)9798350344837

In the dynamic landscape of online knowledge exchange, platforms such as Quora have become vital arenas for diverse discussions and information dissemination. However, distinguishing sincere from insincere questions poses a challenge, impacting user experience and content credibility. The research seeks to utilize BERT-based frameworks to classify Quora questions, with a specific focus on discerning between sincere and insincere inquiries. The study underscores the significance of automated insincere content identification in fostering a trustworthy and constructive online environment on Quora, thereby contributing to the improvement of online interaction quality. The research delves into a comprehensive methodology, including data preprocessing, model training, fine-tuning, and performance evaluation. Extensive experimentation demonstrates that the proposed BERT-based approach achieves an impressive F1-score of 96.1%, outperforming existing methods. The contribution of the study lies in its potential to enhance online interactions by automating the identification of insincere content, fostering a conducive environment for meaningful conversations. © 2024 IEEE.

关键词： Information dissemination

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