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Predicting Diabetic Retinopathy Severity with Deep Learning: A Survey of Fundus Image Analysis Technique 10

Predicting Diabetic Retinopathy Severity with Deep Learning:...

引用

10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Sornil, A. Binusha Sheeja Herobin Rani, C. Sheeba, I.Rexilin C.S.I Institute of Technology Dept. of Information Technology Nagercoil Thovalai India St.Xaviers Catholic College of Engineering Dept. of Electronics and Communication Engineering Chunkankadai Nagercoil India Sathyabama Institute of Science and Technology Dept. of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350353068

Diabetic retinopathy (DR) is a significant complication of diabetes mellitus, impacting vision due to retinal abnormalities. Early detection and precise severity assessment are crucial for effective management. Leveraging deep learning techniques and image preprocessing methods, this paper proposes a comprehensive approach to DR classification. Utilizing publicly available datasets like EyePACS, Messidor-2, APTOS, and DDR, preprocessing steps including Gaussian blurring and data augmentation are employed to enhance image quality and address class imbalance. Wavelet decomposition is used for feature extraction to capture multi-resolution information from fundus images. Transfer learning with ResNet variants, coupled with regularization techniques, aids in model generalization. A modified ResNet50 architecture is introduced, featuring custom fully connected layers and additional convolutional layers for improved feature extraction. The model aims to classify retinal diseases into four severity levels: normal, mild, moderate, and severe proliferative. The survey aspect delves into preprocessing methods' effectiveness in improving CNN performance for medical image analysis, specifically in DR detection. The applicability of transfer learning in medical imaging tasks, particularly in DR, is also explored. This study contributes to advancing medical image analysis for DR diagnosis and classification, addressing the critical need for efficient detection and management of this debilitating condition. © 2024 IEEE.

关键词： Feature extraction

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Integrated Guidelines for Enterprise Economic Security Enhancement Amid Digital Transformation 3

Integrated Guidelines for Enterprise Economic Security Enhan...

引用

3rd International Conference on Creative Communication and Innovative technology, ICCIT 2024

作者： Apriani, Desy Apriliasari, Dwi Maharani, Aditya Hidayat, Farhan Julianingsih, Dwi Fahrudin, Rifqi University of Raharja Dept. of Information Systems Tangerang Indonesia Pandawan Sejahtera Indonesia Dept. of Information Systems Tangerang Indonesia Bina Bangsa University Dept. of Information Technology Serang Indonesia Bosindo Dept. of Informatics Engineering Tangerang Indonesia Aptisi Dept. of Retail Management West Jakarta Indonesia Catur Insan Cendekia University Dept. of Information Systems Cirebon Indonesia

ISBN: (纸本)9798350367492

As enterprises undergo rapid digital transformation, securing economic stability amidst evolving threats becomes increasingly complex. This paper introduces a set of integrated guidelines designed to enhance enterprise economic security in this dynamic environment. We systematically explore the interplay between digital advancements and economic security challenges, such as cyber threats, data breaches, and compliance issues. Our approach integrates advanced technological solutions with strategic organizational practices and comprehensive policy frameworks. By evaluating current security paradigms and proposing a holistic security model, we offer a roadmap for enterprises to safeguard their economic interests effectively. The guidelines are validated through real-world case studies and simulations, illustrating their practicality and efficacy in fortifying economic security. This research provides a valuable framework for enterprises aiming to balance digital innovation with robust economic protection. © 2024 IEEE.

关键词： Marketing

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Quantum Inspired Image Classification: A Hybrid SVM Framework 6

Quantum Inspired Image Classification: A Hybrid SVM Framewor...

引用

6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Patel, Heet Kamthekar, Sneha Prajapati, Dinesh Agarwal, Richa Trinity College of Engineering and Research Savitribai Phule Pune University Dept. of Information Technology Pune India

ISBN: (纸本)9798350306613

We propose a Hybrid Quantum Classical Algorithm (HQCA) for image classification using a Quantum Kernel which is efficient to produce than a traditional kernel for performing the kernel trick required in Support Vector Classification. Since classical data cannot be directly provided to a quantum circuit, amplitude encoding is performed on the image matrix. Using the ZZFeatureMap of Qiskit framework we store the extracted feature of the images. ZZFeatureMap is chosen because of its promising behaviour towards providing quantum advantage. Using this feature map we create a quantum kernel which can be fine-tuned to a ground level for a particular data set by the programmers. We use FidelityQuantumKernel class from qiskit library to create the kernel. To reduce the size of the dataset required to train the model we use a image augmentation layer for data expansion. Python library called Augmentor is used for creating this layer. This model can prove to be more accurate and light weight than other quantum counter parts as quantum convolutional neural network. Iterative approach is adopted for the minimization of the loss after each optimization the model is checked for accuracy and efficiency until the threshold is met. With advancement in quantum hardware the precision of such model can be increased. © 2024 IEEE.

关键词： Augmentor Hybrid Quantum Classical Algorithm Quantum Kernel Support Vector Classification ZZFeatureMap

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Pathway Width Estimation Method using Images and Pathway information Provision Method for Wheelchair Users 12

Pathway Width Estimation Method using Images and Pathway Inf...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Kaneda, Kazuyuki Itou, Kengo National Institute of Technology Sasebo College Dept. of Control Engineering Sasebo Japan

ISBN: (纸本)9798350340181

To provide pathway width information and ride comfort information to wheelchair users, we mounted a web camera, an acceleration sensor, and a GPS sensor to a wheelchair. To estimate the path width, we first performed semantic segmentation on the captured images. We then focused on the boundary between the estimated pathway area and other areas in the image, and we propose a simple and automatic pathway width estimation method by extending that boundary line to the wheelchair position. In addition, we evaluated the ride comfort from the obtained acceleration signal, acquired the position information from the GPS signal, and represented this information as lines on a map. We visualized the obtained path information by associating the estimated path width and ride comfort information with the thickness and color of the lines. © 2023 IEEE.

关键词： Wheelchairs

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Study and Analysis of MultiChain Native Asset 10

Study and Analysis of MultiChain Native Asset

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Kharjana, Mebanjop Sahana, Subhas Chandra Saha, Goutam North-Eastern Hill University Dept. of Information Technology Meghalaya Shillong India National Institute of Technology Dept. of Computer Science & Engineering West Bengal Durgapur India

ISBN: (纸本)9798350384369

MultiChain native assets were blockchain-based dig-ital assets created, managed, and traded on its network. Such blockchain assets were ensured to be transparent, secured, and trusted. Different applications used MultiChain assets to represent digital and physical objects like images, files, houses, cars, etc. This paper aimed to highlight the MultiChain platform and how it manages its native assets. This was achieved by demonstrating different MultiChain commands to handle and manage assets. MultiChain native assets were then analyzed based on the existing frameworks for blockchain-based digital assets and tokens. They were also analyzed to study their compliance with different token standards established by Ethereum. Both analyses revealed that the MultiChain native asset is more advanced and compatible with most contemporary token standards. The results of this investigation are useful to guide future applications that utilize MultiChain native assets. © 2024 IEEE.

关键词： Asset Management Bitcoin Blockchain Blockchain Asset Ethereum Token Standard MultiChain Token Framework

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Employing Stereo Convolutional Neural Networks for Precise 3D Object Localization in Autonomous Driving technology 2

Employing Stereo Convolutional Neural Networks for Precise 3...

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2nd International Conference on Cyber Physical Systems, Power Electronics and Electric Vehicles, ICPEEV 2024

作者： Abhilash, P.K. Sahoo, Bidush Kumar Rajasekhar, N. Gandhi Institute of Engineering & Technology University Odisha Gunupur765022 India Dept. of CSE Gandhi Institute of Engineering & Technology University Odisha Gunupur765022 India Dept. of Information Technology GRIET Telangana Hyderabad India

ISBN: (纸本)9798350388664

In this study, we delve into the Stereo Region-based Convolutional Neural Network (Stereo R-CNN) and its application in the real-time detection of objects for autonomous vehicles. Utilizing pairs of images, this advanced framework captures and computes the precise positioning of objects in a three-dimensional context, an essential component for the sophisticated navigation and safety systems integral to driverless cars. The paper meticulously analyzes the Stereo R-CNN's structure, emphasizing the strategic implementation of the Stereo Regional Proposal Network (Stereo RPN), the precision of key point prediction methodologies, and the accuracy of 3D bounding box construction. Our research offers a comprehensive review of the network's performance through rigorous testing across a variety of driving conditions. The findings reveal that the Stereo R-CNN significantly outperforms conventional monocular image detection approaches, underscoring its potential to revolutionize object detection in the realm of autonomous driving. This paper aims to present a clear and concise understanding of Stereo R-CNN's capabilities and the substantial advancements it brings to autonomous vehicle technology. © 2024 IEEE.

关键词： Convolutional neural networks

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Design and Performance Analysis of a 38 GHz Microstrip Patch Antenna with Slits Loading for 5G Millimeter-Wave Communications 3

Design and Performance Analysis of a 38 GHz Microstrip Patch...

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3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023

作者： Ali, Mohammed A. M. Gaid, AbdulGuddoos S. A. Saeed, Mamoon M. Saeed, Rashid A. Taiz University Faculty of Engineering & Information Technology Dept. of Communications & Computer Taiz Yemen Faculty of Engineering Dept. of Communications & Electronics Engineering Sana'a Yemen College of Computers and Information Technology Taif University Dept. of Computer Engineering Taif21944 Saudi Arabia

ISBN: (纸本)9798350305333

In this paper, we present a compact, rectangular microstrip patch antenna with small rectangular slits designed for 5G wireless applications in the 38GHz band. The antenna is built on a Roger RT duroid 5880 substrate with a relative permittivity of 2.2, a height of 0.381 mm, and a loss tangent of 0.0009. The microstrip line technique is utilized for power feeding to the radiating patch. To enhance the antenna's performance, three slits are incorporated into the front side of the radiating patch. The design, simulations, and optimizations are conducted using the High-Frequency Structure Simulator (HFSS), while Computer Simulation technology (CST) is used for validating the HFSS results. The antenna has a compact overall size of 6.12 × 6 × 0.381 mm3. Moreover, the proposed antenna exhibits impressive characteristics, including a resonance frequency of 38.67 GHz, a reflection coefficient (S11) of - 47.82 dB, and an impedance bandwidth of 2.35 GHz (37.45 GHz - 39.8 GHz). In addition, the antenna's gain varies from 7.84 dBi at the lower frequency of the operational band to 7.9 dBi at the higher frequency, with a maximum gain of 8.037 dBi at the resonance frequency. Likewise, the radiation efficiency is above 99% across the operational band. The results obtained from both simulators are in a good agreement and surpass those of many previously published antennas, indicating that the proposed antenna is a promising solution for 5G wireless communication applications. © 2023 IEEE.

关键词： Millimeter waves

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

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1st International Conference on Robotics, engineering, Science, and technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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Efficiency Redefined: The Document Scanner App for Precise Entity Identification with Customized NER 3

Efficiency Redefined: The Document Scanner App for Precise E...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Javid, Sajid Saim, Mohammad Islam, Saiful Indraprastha Institute of Information Technology Delhi Dept. of Computer Science & Engineering Delhi India University of Cincinnati Dept. of Computer Science & Engineering CincinnatiOH United States Zakir Husain College of Engineering & Technology Aligarh Muslim University Dept. of Computer Engineering Aligarh India

ISBN: (纸本)9798331518592

In the era of rapid advancements in technology, the efficient digitization of paper-based documents remains a crucial challenge across various domains. The traditional approach to document scanning often struggles with accurate extraction of critical information from unstructured or diverse document formats. This paper presents the development of a web-based document scanner application that leverages Named Entity Recognition (NER) to extract entities from scanned business cards efficiently. The study aims to address the challenge of digitizing and organizing physical documents, with a focus on precise entity extraction. The methodology involves creating a custom dataset of scanned business cards, preprocessing the data, and training an NER model using machine learning techniques. The application is built using the Flask framework and integrates OpenCV for text extraction and SpaCy for NER. The key findings include the model's high F1 score in identifying entities such as names, organizations, designations, emails, and contact details. The application streamlines document digitization by automatically extracting and tagging relevant metadata, minimizing the need for manual data entry. This research contributes to enhancing document management and demonstrates broader applicability for other document types apart from business cards. The implications highlight improvements in workflow automation, data accuracy, and the potential for integrating with larger document management systems. © 2024 IEEE.

关键词： Optical character recognition

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Framework for Optimizing Distribution of Deep Neural Network Inference Tasks across Computing Networks

Framework for Optimizing Distribution of Deep Neural Network...

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2024 International Symposium on Networks, Computers and Communications, ISNCC 2024

作者： Preetha Evangeline, D. Sahu, Atma R. Anandhakumar, P. Siva Subramaniya Nadar College of Engineering Dept. of Information Technology Tamil Nadu Kalavakkam India Coppin State University Dept. of Mathematics and Computer Science BaltimoreMD United States Madras Institute of Technology Anna University Dept. Of Information Technology Tamil Nadu India

ISBN: (纸本)9798350364910

Ubiquitous artificial intelligence (AI) is considered one of the key services in 6G systems. AI services typically rely on deep neural networks (DNN) requiring heavy computation. Hence, to support ubiquitous AI, it is crucial to provide a solution for offloading or distributing computational burden due to DNN, especially at end devices with limited resources. This paper proposes an optimization framework for assigning the tasks of DNN layer computations to computing resources in the network, to reduce the inference latency. To this end, we propose a layered graph model with which simple conventional routing jointly solves the problem of selecting nodes for computation and paths for data transfer between nodes. The proposed framework is applied to derive algorithms for minimizing the end-to-end inference latency. The numerical evaluations show that our new formulation can find a solution for DNN inference job distribution much faster than the existing formulation and that our algorithms can select computing nodes and data paths adaptively to the computational attributes of given DNN inference jobs. © 2024 IEEE.

关键词： Computation offloading

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