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Optimizing Diabetic Foot Ulcer Detection: Leveraging SSD and YOLO Architectures 21

Optimizing Diabetic Foot Ulcer Detection: Leveraging SSD and...

21st IEEE International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2024

作者： Azeem, Muhammad Zaman, Muhammad Akhunzada, Adnan Kehkashan, Tanzila Ashraf, Imran Rehman, Abdul The University of Lahore Department of Computer Science Sargodha Pakistan COMSATS University Islamabad Department of Computer Science Islamabad Pakistan University of Doha for Science and Technology Department of Data and Cybersecurity Doha24449 Qatar Universiti Teknologi Malaysia Faculty of Computing Johor Bahru Malaysia The University of Lahore Faculty of Computer Science Sargodha Pakistan

ISBN: (纸本)9798350378078

Diabetic foot ulcer (DFU) are a severe complication in diabetic patients, requiring accurate and early diagnosis to prevent further complications such as infection or amputation. To address this, Research employed YOLO and SSD models for automated DFU detection from medical images, comparing their performance based on key evaluation metrics, including accuracy, precision, recall, and F1-score. Results demonstrate that both models perform exceptionally well, with SSD achieving an accuracy of 98.7%, surpassing YOLO's 97.5%. Additionally, SSD exhibited superior precision (99%), recall (98.9%), and F1-score (99.1%), indicating its robustness in detecting ulcerated regions of varying sizes and stages. These results were further contextualized through a comparison with previous studies, where SSD outperformed several CNN-based models, which achieved accuracy ranging from 93.7% to 97.0%. The SSD model's multi-scale object detection capabilities, combined with transfer learning and data augmentation techniques, contributed to its high performance. Overall, this study demonstrates the potential of deploying SSD and YOLO models in clinical settings for early and accurate DFU detection, paving the way for more reliable and timely interventions in diabetic care. The findings underline the significance of advanced object detection methods, offering promising avenues for improving patient outcomes in medical imaging © 2024 IEEE.

关键词： Diagnosis

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PandoraGAN: Generating Antiviral Peptides Using Generative Adversarial Network

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SN Computer science 2023年第5期4卷 1-13页

作者： Surana, Shraddha Arora, Pooja Singh, Divye Sahasrabuddhe, Deepti Valadi, Jayaraman Engineering for Research Thoughtworks Technologies Maharashtra Pune 411006 India Department of Chemical Engineering Indian Institute of Technology Maharashtra Bombay 400076 India Faculty of Computing and Data Science FLAME University Maharashtra Pune 411007 India

The continuous increase in pathogenic viruses and the intensive laboratory research emphasizes the need for cost- and time-efficient drug development. This accelerates research for alternate drug candidates like antiviral peptides (AVP) that have therapeutic and prophylactic potential and gaining attention in recent times. However, diversity in their sequences, limited and non-uniform characterization often limit their applications. Isolating newer peptide backbones with required characteristics is a cumbersome process with many design–test–build cycles. Advanced deep learning approaches such as generative adversarial networks (GAN) can be helpful to expedite the initial stage of developing novel peptide drugs. In this study, we developed PandoraGAN that uses a manually curated training dataset of 130 highly active peptides that include peptides from known databases (such as AVPdb) and literature to generate novel antiviral peptides. The underlying architecture in PandoraGAN is able to learn a good representation of the implicit properties of antiviral peptides. The generated sequences from PandoraGAN are validated based on physico-chemical properties. They are also compared with the training dataset statistically using Pearson’s correlation and Mann–Whitney U-test. We, therefore, confirm that PandoraGAN is capable of generating a novel antiviral peptide backbone showing similar properties to that of the known highly active antiviral peptides. This approach exhibits a potential to discover novel patterns of AVP which may have not been seen earlier with traditional methods. To our knowledge, this is the first ever use of GAN models for antiviral peptides across the viral spectrum. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Antiviral peptide Drug discovery GAN Generative models Peptide therapeutics

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Intelligent Systems Design and Applications 1

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Ajith Abraham Sabri Pllana Gabriella Casalino Kun Ma Anu Bajaj

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Intelligent Systems Design and Applications 1

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Ajith Abraham Sabri Pllana Gabriella Casalino Kun Ma Anu Bajaj

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Intelligent Systems Design and Applications 1

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Ajith Abraham Sabri Pllana Gabriella Casalino Kun Ma Anu Bajaj

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Generative Adversarial Networks for Spatio-Spectral Compression of Hyperspectral Images 14

Generative Adversarial Networks for Spatio-Spectral Compress...

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14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2024

作者： Fuchs, Martin Hermann Paul Byju, Akshara Preethy Walda, Alisa Rasti, Behnood Demir, Begum Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri India Technische Universität Berlin Faculty of Electrical Engineering and Computer Science Germany BIFOLD - Berlin Institute for the Foundations of Learning and Data Germany

ISBN: (纸本)9798331513139

Deep learning-based hyperspectral image (HSI) compression has recently attracted great attention in remote sensing due to the growth of hyperspectral data archives. Most of the existing models achieve either spectral or spatial compression and do not jointly consider the spatio-spectral redundancies present in HSIs. To address this problem, in this paper, we propose High Fidelity Compression (HiFiC)-based models for spatio-spectral compression of HSIs. In detail, we introduce two new models: i) HiFiC using Squeeze and Excitation (SE) blocks (denoted as HiFiCsE);and ii) HiFiC with 3D convolutions (denoted as HiFiC3D) in the framework of compression of HSIs. We analyze the effectiveness of HiFiCsE and HiFiC3D in compressing the spatio-spectral redundancies with channel attention and inter-dependency analysis. Experimental results show the efficacy of the proposed models in performing spatio-spectral compression, while reconstructing images at reduced bitrates with higher reconstruction quality. The code of the proposed models is publicly available at https://***/rsim/HSI-SSC. © 2024 IEEE.

关键词： Generative adversarial networks

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Intelligent Systems Design and Applications 1

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Ajith Abraham Sabri Pllana Gabriella Casalino Kun Ma Anu Bajaj

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PraK Tool: An Interactive Search Tool Based on Video data Services 30th

PraK Tool: An Interactive Search Tool Based on Video Data S...

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30th International Conference on MultiMedia Modeling, MMM 2024

作者： Lokoč, Jakub Vopálková, Zuzana Stroh, Michael Buchmueller, Raphael Schlegel, Udo SIRET Research Group Department of Software Engineering Faculty of Mathematics and Physics Charles University Prague Czech Republic Visual Computing Department of Computer Science Faculty of Natural Sciences Konstanz University Konstanz Germany Data Analysis and Visualization Department of Computer Science Faculty of Natural Sciences Konstanz University Konstanz Germany

ISBN: (纸本)9783031533013

This paper presents a tool relying on data service architecture, where technical details of all VBS datasets are completely hidden behind an abstract stateless data layer. The data services allow independent development of interactive search interfaces and refinement techniques, which is demonstrated by a smart front-end component. The component supports common search features and allows users to exploit content-based statistics for effective filtering. We believe that video data services might be a valuable addition to the open-source VBS toolkit, especially when available for the competition on a shared server with all VBS datasets, extracted features, and meta-data behind. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Video recording

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Key-dependent Advanced Encryption Standard

Key-dependent Advanced Encryption Standard

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2018 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2018

作者： Altigani, Abdelrahman Hasan, Shafaatunnur Barry, Bazara Shamsuddin, Siti Mariyam UTM Big Data Centre Universiti Teknologi Malaysia Skudai Johor Malaysia Faculty of Computing Universiti Teknologi Malaysia Skudai Johor Malaysia Departement of Computer Science University of Khartoum Khartoum Sudan

ISBN: (纸本)9781538641231

Rijndael has been selected by the National Institute for Standards and Technology (NIST) as the Advanced Encryption Standard (AES). In compliance with Kerckhoffs's principle, and to preserve and promote interoperability, the design and internal operation of AES must remain open. However, we suggest that there is no need to retain the static nature of the design. Consequently, this research paper main objective is to introduce a dynamic algorithm, that determines the exact steps used for encrypting or decrypting payloads during execution time. This has been achieved by making AES parameters key dependent, rather than reuse fixed, pre-determined *** result is an armored version of the AES that changes its internal design with almost every new encryption key. The proposed design is provided and analyzed in terms of security, implementation cost and possibility for further improvements. © 2018 IEEE.

关键词： Cryptography

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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