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Impact of Novel Pre-Processing Techniques on Retinal Images 2

Impact of Novel Pre-Processing Techniques on Retinal Images

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Sahu, Deepti Kaur, Mandeep Sharda University Dept. of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798350371055

Glaucoma, a gradually developing eye condition that can damage the optic nerve, is one of the leading causes of irreversible blindness worldwide. The detection of glaucoma is required in its initial phases for the prevention of the disease. Several machine learning and deep learning models have been developed to detect the disease. These models require a preprocessed structured data set for better efficiency and accuracy of detection. The image datasets used for this purpose have been found with several issues of outliers and noise that limit the accuracy of the results. Hence, proper handling of the dataset in terms of pre-processing is vital. This paper presents a novel pre-processing technique for better glaucoma detection as it is necessary to remove outliers from the retinal images. The proposed 'EMF' model for pre-processing comprises Enhancement, Morphology, and Filtering of the images to get better results on the Retina. Drishti dataset has been used to evaluate the efficiency of the proposed technique. This dataset has several outliers that limit the accuracy, making it difficult to diagnose glaucoma. However, with the usage of the proposed technique, the dataset could be efficiently utilized for glaucoma detection. Compared to current state-of-the-art techniques, the findings from the proposed approach were shown to be better in terms of MSE, PSNR, and entropy. © 2024 IEEE.

关键词： Frequency domain Glaucoma Pre-processing Region of interest Retinal image Spatial domain

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Real-Time Stress Detection Using Facial Images and Convolutional Neural Networks

Real-Time Stress Detection Using Facial Images and Convoluti...

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2024 IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2024

作者： Sindu, M. Ashwin, T. Shyam Sunder, V. Shivasankaran, S. Poongothai, P. Ponnusamy, R. Chennai Institute of Technology Dept. of Computer Science and Engineering Tamil Nadu India Chennai Institute of Technology Dept. of Computer Mathematics Tamil Nadu India

ISBN: (纸本)9798331535476

Stress is one of the prevailing issues in today's world, deeply impacting the actual well-being of individuals. In this paper, we introduce an innovative method to detect stress that deviates from the mainstream approaches, which rely solely on physiologic signals and self-reporting. Our non-invasive, efficient, and scalable real-time system, built on the facial image data processed by CNNs, makes real-time human stress detection possible. The system captures facial expressions through video or static images, which it then processes within a CNN model to identify stress-related features. CNNs are particularly innovative in that they are adept.at automatically extracting and learning hierarchical features from extremely complex, unstructured data like facial images. Facial expression datasets were used to train and test the proposed model in different stress conditions. The model achieved a very good accuracy level in differentiating stressed from non-stressed states, thus putting it on par with professionals. Real-time testing of the system's performance was done on edge devices such as smartphones to prove its potential for use in real-life applications related to mobile health. As facial image data is utilised by the system, thereby killing the need for wearable sensors or invasive physiological monitoring, the approach would be more accessible for detecting stress levels. This research showed that CNN models developed based on facial images can transform stress monitoring. Its implications are wide, applicable in health care, workplace settings, and even self-manageable personal stress. In future work, the model should be generalised for diverse populations, the system's real-time capabilities enhanced, and multimodal data further integrated to increase detection accuracy and reliability. © 2024 IEEE.

关键词： Convolutional neural networks

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Predicting electrically evoked action potentials in image-based cochlear implants models using ResNet

Predicting electrically evoked action potentials in image-ba...

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Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Vu, Minh Bratu, Erin L. Noble, Jack H. Dept. of Electrical Engineering and Computer Engineering Vanderbilt University NashvilleTN37235 United States

ISBN: (纸本)9781510685949

Cochlear implants (CI) are highly successful neural-prosthetic devices, recreating the sensation of hearing for individuals experiencing severe to profound hearing loss. CI user experiences vary greatly due to several reasons, with changes in neural health within the cochlea being a major contributing factor. Estimating a patient's auditory neural health is thus very important for patient-specific programming. One common method used to derive the number of healthy auditory nerve fibers (ANF) is through electrically evoked compound action potential (ECAP). Comparison between clinically measured ECAP responses and simulation can provide insights into a patient's neural health condition. This simulation is currently done through in-house software that calculates simulated nerve fibers' responses to stimulation but is very time-consuming. In this work we attempt to generate ECAP response using ResNet18 trained on the in-house ECAP simulations of 6 patients, augmented with varying resistivity parameters and CI locations. Our goal is to reduce computation time, allowing for model creation and patient-specific programming recommendations during a single patient visit, while also eliminating common problems with outliers and artifacts during ECAP simulation. Our method generated ECAP responses with peaks that were within 10% of the traditional model output on average, unaffected by stimulus artifacts, and with an average inference time of 1.12 ±0.08 s. This represents a large decrease in computational overhead for our procedure and could facilitate same-day patient-specific programming. © 2025 SPIE

关键词： Neurology

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Rough Set Based Recipe Clustering Approach 10

Rough Set Based Recipe Clustering Approach

引用

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

作者： Das, Priyanka Mukherjee, Chandrani Gupta, Samiksha Roy, Sayan Shah, Khushi Singh, Shreya Institute of Engineering & Management Dept. of Computer Application and Science Kolkata India

ISBN: (纸本)9798350384369

Online cooking instructions including ingredient lists and cooking methods are now widely available due to the proliferation of recipe sharing websites. Finding novel and complex patterns in such vast, ambiguous categorical data sets is a crucial task. Conventional clustering analysis algorithms frequently fail to address the uncertainty surrounding the exact value of features found in these categorical data sets. Thus to aid in decision-making, rough set based clustering is frequently used. This study aims to identify the optimal clustering feature from the recipe data that will result in the grouping of related food products by applying the rough purity notion. The recipe data has been regarded as a categorical valued information system in this instance, and information theoretic attribute purity is taken into account using the rough purity technique. © 2024 IEEE.

关键词： Food chemistry

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Medlet-Block: Secured Health-Based Cloudlet Platform Using Blockchain 16

Medlet-Block: Secured Health-Based Cloudlet Platform Using B...

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16th International Conference on COMmunication systems and NETworkS, COMSNETS 2024

作者： Gupta, Atrayee Agarwal, Varun Techno Main Saltlake Dept. of Computer Science and Engineering Kolkata India

ISBN: (纸本)9798350383119

Medical information cannot be easily shared and exchanged between various healthcare systems and providers due to a lack of interoperability, delays, inefficiencies, and above all lack of security. This paper provides a design of an edge-based blockchain for a secured health-care system which takes care of confidentiality, integrity, non-repudiation and other security challenges. © 2024 IEEE.

关键词： Block Health-care Symmetric key Transaction

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ImportChainBD: Blockchain Solutions for Transparent and Accountable Imported Cosmetic Products 3

ImportChainBD: Blockchain Solutions for Transparent and Acco...

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3rd IEEE International Conference on Blockchain and Distributed systems Security, ICBDS 2024

作者： Khan, Md. Adib Karmoker, Sagar Rumpa, Ummay Khadiza Rahman, Habibur Hossain, Md. Sabbir Anik, Nur Adnan Chowdhury Hasan, Mahamudul East West University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350354348

To improve the supply-chain management system of Bangladesh for imported cosmetic products this paper proposes a blockchain-based solution. One of the major goals of this project is to increase the tax compliance of the government by stopping counterfeit and illegally imported cosmetic products. Which will enhance the trust of consumers and the brand's reputation. Using this system is quite easy and convenient, as All the information will be stored in the blockchain, so it will become a secure and immutable product tracking system for importers, distributors, and retailers to maintain their ledgers just by printing and scanning a QR code through an IoT device, and consumers can check the authenticity of these cosmetic products just by scanning them. If the product is verified to be suspicious, The Mobile Court Management System has the power to check its origin. Finally, we can say that it will avoid the sale of counterfeit items in the market and increase government revenue on tax. © 2024 IEEE.

关键词： Cosmetics

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'RNN-Driven Prognosis of Heart Disease Based on Health Parameters' 2

'RNN-Driven Prognosis of Heart Disease Based on Health Param...

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

作者： Rahi, Parvez Singh, Inderjeet Singh, Ajay Pal Kumar, Alok Chandigarh University Dept. of Computer Science & Engineering Punjab Mohali India

ISBN: (纸本)9798331519056

Cardiovascular diseases (CVD) are the leading cause of death globally and are estimated to affect 17. 9 million deaths annually. Early diagnosis is very important if one is to prevent adverse consequences. However, traditional diagnostic methods can take time to complete and miss subtle trends in patient information. This research presents an innovative approach utilizing a Recurrent Neural Network (RNN) model, optimized through Stochastic Gradient Descent (SGD), for the prediction of seven distinct types of heart disease: CAD, Heart Failure, AFib, Hypertensive Heart Disease, Congenital Heart Disease, Cardiomyopathy, and PAD. Their architecture is specifically suited for direct modeling of sequential patterns of the health related data that in turn helps to detect temporal patterns and changes in them. This model use ReLU activation function in their hidden layers, dropout in preventing overfitting and batch normalization for stable learning. Moreover, the feature augmentation is used in the model making it use various psychological and physiological parameters that help in making comprehensive predictions on the risks of heart disease. After training the RNN with a Kaggle dataset and properly tuning it, the model obtained an accuracy level of 91%, which means that is highly useful in identifying risk factors of cardiovascular diseases and could be used for early diagnosis and risk factors identification. © 2024 IEEE.

关键词： Recurrent neural networks

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A New Half-Bridge/Dual-Stacked-Switches Structured Electrolytic Capacitor-less AC/DC Bi-Directional On-Boad Charger for High-Voltage EV Battery

A New Half-Bridge/Dual-Stacked-Switches Structured Electroly...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Derakhshan, Siamak Lam, John York University Dept. Electrical Engineering and Computer Science Toronto Canada

ISBN: (纸本)9798350376067

This paper introduces a novel half-bridge (HB)/dual-stacked-switches based electrolytic capacitor-less bidirectional AC/DC converter for high voltage (HV) electric vehicle (EV) systems. The proposed two-stage AC/DC converter incorporates a closed-loop Power Factor Correction (PFC) mechanism based on the dq model of the input LCL filter, ensuring high-quality input current with minimized Total Harmonic Distortion (THD) during both conversion and inversion operations of the converter. Moreover, the front-end HB PFC circuit operates in Continuous Conduction Mode (CCM) that results in the elimination of the high peak current in the switches. Additionally, a dedicated closed-loop control system is deployed in the dual-stacked-switches resonant converter to significantly reduce the output voltage ripple, thus eliminating the use of bulky electrolytic-type storage capacitors. Output voltage regulation is realized by using Variable Frequency Modulation (VFM). Soft-switching operation is guaranteed for all the switches and diodes using CLLC resonant circuit for both conversion and inversion modes of operation. The proposed circuit's performance is verified through a 1kW, 120Vrms/800Vdc proof-of-concept prototype. © 2024 IEEE.

关键词： Electrolytic capacitors

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Model-Based Web Service Development Using Discrete Event systems

Model-Based Web Service Development Using Discrete Event Sys...

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2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Lee, Sunmin Lee, Minji Kim, Taehoon Jang, Sooyoung Choi, Changbeom Hanbat National University Dept. of Computer Engineering Daejeon Korea Republic of

ISBN: (纸本)9798331530839

A modern web service consists of two key components: a front-end and a back-end system. The front-end handles user interactions and forwards requests to the back-end. The back-end processes these requests, generates the necessary data or responses, and sends them back to the user through the front-end. Therefore, developing effective web services requires careful design of both the front-end and back-end systems, as well as the interface between them. This study focuses on the front-end and proposes a notation to represent it as discrete event systems, addressing challenges related to HTML syntax complexity and link modification. © 2024 IEEE.

关键词： Web services

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Bio-Inspired Tree Seed Algorithm Enhanced Discrete Wavelet Technique for Memory Control 4

Bio-Inspired Tree Seed Algorithm Enhanced Discrete Wavelet T...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： More, Sachin D Ingle, Dayanand Bharati Vidyapeeth College of Engineering University of Mumbai Dept. of Computer Engineering Navi Mumbai India

ISBN: (纸本)9798331523923

The widely recognized classical image compression techniques are renowned for their excellent performance, minimal computational complexity, and the ability to generate an embedded bitstream that can be decoded at varying bit rates, resulting in progressively improved image quality as more bits are received. It requires a significant amount of computer memory as it stores the generated sets and the pixel locations in linked lists. The multiresolution feature of transform does not result in the creation of a resolution-scalable bitstream that would allow the image to be decoded at various resolutions. The enormous memory issue with the conventional methods is resolved by the Tree Seed Algorithm (TSA) an Enhanced Discrete Wavelet Transform methodology which requires just one list of fixed size with average of 2.25 bits/pixel and size of 1/4 of the image. The primary contribution of this study lies in enhancing image quality and resolution thereby optimizing memory usage. The TSA Optimized Discrete Wavelet Transform approach is recommended in this study to decrease complexity and improve processing speed. Using the unique attributes of the algorithm, it is particularly well-suited to meet the diverse skill levels and resolution preferences of contemporary Internet users. © 2025 IEEE.

关键词： Decoding

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