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Remote Sensing Aircraft Classification Harnessing Deep Learning Advancements 18

Remote Sensing Aircraft Classification Harnessing Deep Learn...

引用

18th IEEE International Conference on Emerging Technologies, ICET 2023

作者： Saeed, Ahmad Atif, Haasha Bin Habib, Usman Bilal, Mohsin National University of Computer and Emerging Sciences Dept. of Ai & Data Science Islamabad Pakistan

ISBN: (纸本)9798350328172

Remote sensing imagery is challenging to analyze due to its diverse sources, object image variability and contextual backgrounds. In current era, Aviation Industry is continuously progressing from specific domain of aircraft classification to improving in its safety measures, maintenance procedures and diverse flight operations by utilizing the potential of satellite imagery and Deep Learning methods. This paper highlights and explores the potential of Transfer Learning with state-of-the-art Deep Learning architectures on publicly available Multi Type Aircraft Remote Sensing Imagery datasets. In the same context, our experiments and training mechanism on the state-of-the-art models, like Vision Transformers, ResNet50v2, EfficientNetB0 and InceptionNetV3 outperforms earlier methods on the benchmark remote sensing military aircraft dataset. Our experiments on mentioned Deep learning models yielded, 95%, 93.4%, 92% and 80% classification accuracy due to advance architecture design and fine tuning techniques by allowing them to capture more intricate features and patterns of multifaceted military platforms. This research will provide a valuable resource in the aviation industry in the perspective of aircraft recognition domain by utilizing the power of advance Deep Learning methods to handle the complexity and diversity of remote sensing imagery. © 2023 IEEE.

关键词： Remote sensing

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Exploring Climate Change Prediction Dynamics Using Machine Learning Approach: A Review 1

Exploring Climate Change Prediction Dynamics Using Machine L...

引用

1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Tiwari, Shashank Verma, Shikha Chauhan, Rosey Gupta, Neha Sharda Unviersity Dept. of Computer Science Gerater Noida India ABES Engineering College Dept. of Computer Science UP Ghaziabad India

ISBN: (纸本)9798350353648

Climate refers to the long-term weather patterns of a region. Variations in the weather have a lot of implications on our daily lives. Explore the application of deep learning techniques in climate prediction and related fields. It focuses on Long Short-Term Memory (LSTM) models for forecasting air quality, greenhouse temperature control, and urban flood water accumulation using Gradient Boosted Decision Trees (GBDT). The analysis concludes that deep learning, particularly LSTM, offers promising accuracy for various climate-related predictions. Challenges such as data scarcity, non-stationarity, and high dimensionality are addressed, highlighting the need for advanced models to capture complex climate system dynamics and human influences. © 2024 IEEE.

关键词： Prediction models

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Towards the Compilation of Digital Twin Models for Service-Oriented Systems 34

Towards the Compilation of Digital Twin Models for Service-O...

引用

34th Annual International Conference on Collaborative Advances in Software and Computing, CASCON 2024

作者： Jiang, Hao Kontogiannis, Kostas Western University Computer Science Dept. LondonON Canada York University Dept. of Electrical Eng. & Computer Science TorontoON Canada

ISBN: (纸本)9798331504830

Service-oriented architecture (SOA) serves as a foundational technology for complex IT systems, such as e-commerce platforms, banking solutions, public-sector applications, and gaming systems. As these systems become increasingly intricate, the need for models that enable software engineers to simulate component interactions early in the software lifecycle becomes crucial. This approach helps identify potential issues during the design phase. The goal of this research is to apply digital twin model principles to simulate component transactions, message exchanges, and ultimately evaluate whether a given design meets the goals and requirements of stakeholders. In this paper, we outline ongoing work towards a prototype framework that uses sequence diagrams and activity diagrams to build digital twin models of service-oriented systems. The framework aims to ensure that any design changes are reflected in the digital twin model early in the software lifecycle, potentially uncovering non-compliant or unintended interactions. © 2024 IEEE.

关键词： Service oriented architecture (SOA)

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Privacy-Enhanced Image Restoration in Remote Sensing via Federated Learning 12

Privacy-Enhanced Image Restoration in Remote Sensing via Fed...

引用

12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Jahanzeb Khan, M. Rath, Suman Zaib, Muhammad Hassan University of Nevada Reno Dept. of Computer Science and Engineering Reno United States Air University Dept. of Computer Science Islamabad Pakistan

ISBN: (纸本)9798350330366

This research addresses the dual challenges of image restoration quality and data privacy in optical remote sensing. Traditional restoration methods often fall short due to the complex nature of remote sensing images, and data privacy concerns further complicate the use of advanced techniques. By integrating the Deep Memory Connected Neural Network (DMCN) with the data-Decoupled Federated Learning (DDFL) framework, our approach enables significant improvements in image restoration without requiring direct access to sensitive raw data. This method not only enhances data privacy by leveraging federated learning principles but also incorporates advanced techniques like Gaussian image denoising to maintain high restoration quality despite potential noise introduced by the federated process. The performance of the federated DMCN, particularly on the UCMERCED dataset, demonstrates minimal accuracy degradation, even in the presence of noise, while the strategic use of Downsampling Units within DMCN optimizes computational efficiency. Our comprehensive evaluations reveal the effectiveness of this approach in balancing data privacy with the need for high-quality image restoration, suggesting a promising direction for future advancements in remote sensing applications. © 2024 IEEE.

关键词： Image reconstruction

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Formal Modeling and Verification of Justification and Finalization of Checkpoints in Ethereum 2.0 Beacon Chain 1

Formal Modeling and Verification of Justification and Finali...

引用

1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Rashid, Muhammad Rasool, Imran Zafar, Nazir Ahmad Afzaal, Hamra Comsats University Islamabad Dept. of Computer Science Sahiwal Campus Pakistan Information Technology University Dept. of Computer Science Lahore Pakistan

ISBN: (纸本)9798350373042

New to the Ethereum platform with version 2.0 is the Beacon chain. Validator status, attestation information, and many more are maintained via the proof-of-stake (PoS) consensus protocol, which is relied upon. The Ethereum 2.0 beacon chain relies on the validation and completion of checkpoints to validate and finish all the blocks associated with those checkpoints. By formally verifying it using the SPIN model checker, this research tackles the issue of the dependability and security of the Beacon Chain's justification and finalization operations. Due of its novelty (launched in 2020), there is little any literature on the subject. Additionally, no previous study has formally verified the beacon chain using the SPIN model checker. The study makes use of PROMELA, a formal specification language, to formally outline the reasoning and finalization method of the Ethereum 2.0 Beacon Chain. Utilizing the SPIN Model Checker, a program graph is generated for this procedure, which formulaically expresses safety features via the use of linear temporal logic (LTL). To make sure everything is in order, we run the SPIN model checker with the program graph and LTL formulae as inputs to see whether the program graph satisfies the properties. This is the formal verification process. © 2024 IEEE.

关键词： Model checking

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Utilization of Decentralized Finance (DeFi) and Distributed Ledger Technology (DLT) in Banking operations

Utilization of Decentralized Finance (DeFi) and Distributed ...

引用

2024 International Conference on Intelligent Computing and Sustainable Innovations in Technology, IC-SIT 2024

作者： Kumar, Ch Sree Singh, Akhilendra Pratap Reddy, K Hemant K National Institute of Technology Meghalaya Dept. of Computer Science Meghalaya India VIT-AP Dept. of Computer Science and Engineering Vijayawada India

ISBN: (纸本)9798350369175

Distributed Ledger Technology (DLT) is a decentralized database system where transactions are recorded and verified across multiple nodes. Its key features include immutability, time-stamping, and consensus-based validation. Numerous DLT applications are in supply chain management, intellectual property, cross border payments, energy trading, real estate, and online donations. DeFi, a combination of cryptocurrency and blockchain technology, offers financial services without intermediaries. Hence transactions with various digital assets based on cryptocurrency price feeds needs an automated framework. Smart contracts, self-executing contracts with terms directly written into code, automate processes and reduce manual intervention. This paper proposes a decentralized financial trading model using the AAVE protocol. AAVE is a decentralized platform that allows for transactions with various digital assets based on cryptocurrency price feeds. Proposed model uses Chainlink, a decentralized oracle network, to provide accurate and reliable price feeds. IPFS is used for data storage, while Graph is employed for indexing and querying blockchain data. The paper presents an example of a DeFi protocol to simulate banking operations, showcasing the potential of DeFi and DLT in revolutionizing traditional banking processes. © 2024 IEEE.

关键词： Distributed ledger

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WIPP - Smart Authentication: Contextual Strategies for Dynamic User Verification

WIPP - Smart Authentication: Contextual Strategies for Dynam...

引用

2024 Resilience Week, RWS 2024

作者： Sharp, Jonathan Williams, Alexander Womack, Baker Roy, Arunava Dasgupta, Dipankar Farkas, Csilla University of South Carolina Dept. of Computer Science and Eng. United States University of Memphis Dept. of Computer Science United States

ISBN: (纸本)9798350388985

In this paper, we propose a framework to support continuous and adaptive multi-factor authentication. Our proposed solution is based on leveraging the users' context to estimate the risk to the remote login and to support passive user authentication. We have developed a theoretical framework that supports dynamic, context-aware and adaptive selection of the authentication factors. Our Context-Aware and Adaptive Multi-Factor Authentication (CAA-MFA) framework increases the security of remote authentication by selecting k number of factors for the users' authentication in a way that the selected factors are 1) unpredictable by the attackers, 2) satisfy security and privacy constraints, and 3) are suitable for dynamically changing environments. Our current work focuses on implementing a proof-of-concept prototype of the proposed framework. © 2024 IEEE.

关键词： Authentication Protocol

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Enhancing Transaction Security through Iris Recognition 4

Enhancing Transaction Security through Iris Recognition

引用

4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Arepalli, Gopi Suresh Bhavana, Paluvai Krishna, Yakkanti Venkata Sai Surendrababu, Chittibomma Lakireddy Bali Reddy College of Engineering Dept. of computer Science and Engineering Mylavaram India Dept. of Computer Science and Engineering Mylavaram India

ISBN: (纸本)9798350385793

UPI frauds have led to increased use of biometrics for personal identification to ensure security and accuracy. Biometric UPI based on iris recognition technology improves customer service by providing a safe and paperless environment. This system replaces the existing UPI pin and affords protection to the UPI payment from cyber-attacks. During enrollment, genuine user's iris samples and UPI ID are retained in the database, and transactions are completed by capturing and matching iris patterns by using G-6 iris recognizer and biometric Framework. This innovative technology has revolutionized the way to make payments and has significantly reduced the risk of fraudulent activities. With biometric UPI, customers can enjoy a seamless experience when making transactions. The use of biometrics also ensures that there is no chance of identity theft or unauthorized access to sensitive information. © 2024 IEEE.

关键词： Authentication Protocol

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Automated Machine Learning for Information Management and Information Systems: An Overvie 2

Automated Machine Learning for Information Management and In...

引用

2nd International Conference on Cyber Resilience, ICCR 2024

作者： Alduweib, Eman Arqoub, Muhammad Abu Alromema, Waseem University Of Petra Dept. Of Computer Science Amman Jordan Taibah University Dept. Of Computer Science And Information Medina42353 Saudi Arabia

ISBN: (纸本)9798350394962

Recently, linking Machine Learning (ML) to the new trend of Automated Machine Learning (AutoML) is a vital step towards improving the performance of information systems. This research comprehensively explores this new trend, which promotes innovation in ML technologies, facilitates computing, and improves data understanding and utilization. In addition, the study investigates the significant impact of AutoML in the field of Information Systems Management. This paper also discusses the benefits and applications of AutoML, focusing on how these applications contribute to tasks such as automatic data processing, improving data quality, simplifying data integration, and facilitating information retrieval. Moreover, addressing ethical issues, ensuring data security, protecting privacy, validating models are important tasks that arise when using AutoML, which need to be focused on. Looking to the future, we are taking full advantage of AutoML capabilities to innovate information and systems management, make super discoveries, and make more accurate predictions. The purpose of this study is to show the importance, possibilities, and prospects of using AutoML in various information systems. © 2024 IEEE.

关键词： Information management

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Single Object Tracking in Satellite Videos Through Deep Learning and Motion Detection Techniques 6

Single Object Tracking in Satellite Videos Through Deep Lear...

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6th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Hayder, Israa Alizadeh, Fattah Dept. of Computer Science and Engineering University of Kurdistan Hawlere Erbil Iraq Dept. of computer science Toronto Metropolitan university Toronto Canada

ISBN: (纸本)9798350394634

Single object tracking in satellite videos has recently gained a lot of attention in the field of computer vision. Although the satellite images are very informative, the small size of the objects and limited spatial and temporal resolution might make object tracking difficult and inaccurate. In this paper, we propose a method for accurately tracking small objects in satellite videos. In the initial phase, we applied the Fast Super-Resolution Convolutional Neural Network (FSRCNN), a deep learning-based super-resolution technique, to enhance the resolution of the frames. This procedure serves to sharpen the details and features of the objects, resulting in a clearer representation. The main contribution, however, lies in our incorporation of a robust motion detection technique into our framework, marking a significant step forward in this study. The motion detection approach combines various methods and operations with the primary goal of making moving objects distinctly visible and easily distinguishable from the complex image background. This enhancement significantly contributes to the precision and accuracy of the tracking system. We combined both approaches with Fully Convolutional Siamese Network (SiamFC) due to its robustness in tracking processes across frames in videos, capacity to handle changes in target appearance, and ability to deal with small datasets. The Satellite Video Single Object Tracking (SatSOT) and SV248A10-SOT (SV248S), two satellite video single object tracking datasets, were used to evaluate the proposed approach. When the techniques were applied, the SatSOT dataset showed an 11% precision score increase and a 10% success rate improvement. The SV248S dataset exhibited even more significant improvements, with precision scores increasing by 18% and success scores rising by 9%. © 2024 IEEE.

关键词： Satellites

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