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All-in-Focus Imaging using qshiftN DTCWT and LP in the Frequency Partition Domain 9

All-in-Focus Imaging using qshiftN DTCWT and LP in the Frequ...

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9th International Conference on Computing for Sustainable Global Development, INDIACom 2022

作者： Rama Mohan, C. Kiran, S Vasudeva Kumar, A. Ashok Visvesvaraya Technological University Dept. of Computer Science and Engineering Belgaum India Ysr Engineering College of Yvu Dept. of Computer Science and Engineering Proddatur India Nmam Institute of Technology Dept. of Information Science and Engineering Nitte India Ysr Engineering College of Yvu Department of Physics Proddatur India

ISBN: (纸本)9789380544441

Image fusion utilizes fusion rules to combine multifocus images of two or more images of the same scene, which produces a fully focused image. The fusion of images provides vital information about the objects, which is more useful for visual perception and medical diagnosis. Directional selectivity and shift invariance characteristics are found to be very important in the image fusion process. Due to poor shift invariance and directionality, traditional wavelet-based fusion methods create ringing distortions in the fused image. In this paper, a novel multifocus image fusion algorithm based on the quarter shift dual tree complex wavelet transform (qshiftN DTCWT) and laplacian pyramid (LP) in the frequency partition (FP) domain is proposed. Firstly, the source images are decomposed into row and column coefficients with a frequency factor in the FP domain. Secondly, due to its directional and shift invariant characteristics, row and column images are collectively fused with qshiftN DTCWT, which proved to be a very efficient multiresolution transform for image fusion. Finally, to increase the effectiveness of the qshiftN DTCWT in the FP-based method, the LP algorithm is used to produce an all-in-focus image. The result of the proposed strategy reveals the good quality of the fused image due to its better directionality and also reduces artifacts with its shift invariance property. The statistical results also show a better performance of the proposed methodology than that of traditional fusion methodologies. © 2022 Bharati Vidyapeeth, New Delhi.

关键词： Image quality

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ElHa Net: A Pattern Recognition Neural Network

ElHa Net: A Pattern Recognition Neural Network

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Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Elsadig Ahmed Mohamed Babiker Hanan Hassan Ali Adlan Dept. of Computer Science College of Computer Engineering and Science Prince Sattam Bin Abdulaziz University Kharj KSA Dept. of Computer Science Faculty of Mathematical Sciences Uof K Dept. of Computer Science College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh KSA

ISBN: (数字)9798331540104

ISBN: (纸本)9798331540111

Neural Networks are the state-of-the-art models that derive intelligent systems. Generalization of the neural network model is a judge of how well an architecture mimic human intelligence. Self-extraction neural networks become the dominant neural networks, especially in autonomous systems such as intelligent robotics, autonomous vehicles, ⃛ etc. This paper presents a neural network based on distance measure, ElHaNet Neural Network. ElHaNet network is a self-extraction neural network and is capable of pattern recognition. ElHaNet architecture composed of an extraction phase and a classification phase. Neurons in the extraction network capture patterns in the presented input. The classification network performs on the input patterns to be classified according to the problem in hand. The developed architecture is bench marked against well-known architectures for hand written digit recognition. The performance of the network is found to compete favorably with state-of-the-art models in the literature.

关键词： Hands Human intelligence Neurons Pattern recognition Biological neural networks Robots Autonomous vehicles

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Frequency Stability Enhancement in a Fully Solar Power Grid: A Case Study on the Saudi Model

Frequency Stability Enhancement in a Fully Solar Power Grid:...

引用

2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Albukhari, Waleed M. Liu, Yilu Till, Abigail Alshuaibi, Khaled M. University of Tennessee Dept of Electrical Engineering and Computer Science KnoxvilleTN United States Oak Ridge National Laboratory Oak RidgeTN United States King Saud University Dept of Electrical Engineering Riyadh Saudi Arabia

ISBN: (纸本)9798350313604

Recently, renewable energy sources (RES) such as solar photovoltaic (PV) have been recognized for their significant potential. Several studies have explored the issue of frequency stability with high RES penetration. A significant observation related to this issue is the decline in the weighted short circuit ratio (WSCR), which has the potential to adversely affect system stability. This research uniquely focuses on the gradual transition of the Saudi Electricity Company (SEC) system to a fully integrated solar PV grid, offering insight and methodology that can be adapted for other power systems. While a variety of mitigation methods are available, synchronous condensers (SC) were used in this study to stabilize grid frequency, and their implementation has been shown to improve the overall performance of the system. In response to the observed decline in WSCR, a comprehensive short circuit analysis was applied across all regions in the Saudi power grid model to evaluate the reduction in short circuit power and highlight areas requiring enhancement. Scenarios illustrating frequency response with a gradual increase in SCR were analyzed, with the objective of establishing a stable, fully solar PV power system that is resilient to sudden power grid disturbances. © 2024 IEEE.

关键词： Frequency stability

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Proposal for the Support Method Presentation Model Utilizing Nursing Home Insights 9

Proposal for the Support Method Presentation Model Utilizing...

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9th International Conference on Business and Industrial Research, ICBIR 2024

作者： Nakajima, Yoko Yuki, Masamune Ptaszynski, Michal Honma, Hirotoshi Akiba, Tomoyoshi Masui, Fumito Institute of Technology Kushiro Colloege Dept. of Creative Engineering Kushiro Japan School of Regional Innovation and Social Design Engineering of Kitami Institute of Technology Kitami Japan Toyohashi University of Technology Dept. of Computer Science and Technology and Engineering Toyohashi Japan

ISBN: (纸本)9798350383010

One of the significant problems faced by dementia group homes is the high caregiver turnover rate. In particular, there is an urgent need to prevent the turnover of new caregivers and work toward ensuring and improving the quality of care. To address this issue, we are developing a care method support system that utilizes two databases: a personal attributes database and a care case database ([1]-[3]). The personal attributes database extracts personal attributes such as hobbies and previous occupations of residents from care records and care conference minutes. The care case database extracts cases of resident problems, their solutions, and the original text containing them. The care method support system presents candidates for appropriate responses to problems faced by residents based on these databases. In this study, we generated two care suggestion models: Care Suggestion Model: This model applies text similarity to the care case database to suggest candidates for appropriate responses to unregistered problems. Personalized Care Suggestion Model: This model applies clustering to the personal attributes database and generates a care suggestion model that considers personal attributes. We compared the two models and tested the usefulness of the model. © 2024 IEEE.

关键词： Nursing

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Heart arrhythmia detection based on ECG wave classification using neural network and Fuzzy Inference system 2023

Heart arrhythmia detection based on ECG wave classification ...

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15th International Conference on Contemporary Computing, IC3 2023

作者： Waseem, Zoha Haq, Zeeshan Ali Mahto, Anil Kumar Dept. of Computer Science & Engineering SEST Jamia Hamdard New Delhi India Dept of CSE & IT Jaypee Institute of Information Technology UP Noida India

ISBN: (纸本)9798400700224

Detecting the Arrhythmia correctly is an important task in cardiovascular disease detection. Identifying the correct type of arrhythmia provides a fast and effective way for diagnosis. In this paper a neural network based (ANN & CNN) and fuzzy logic based classifiers (ANFIS) are presented and their performance is evaluated using performance evaluation parameters. For this study, MITBIH and PTB diagnostic database are used which provided the total sample size of 1,23,998 ECG waveforms. For classification purpose, features are extracted such as Skewness, Kurtosis, Mean, Standard Deviation, Shannon Entropy, and Energy. In this study, it has been observed that ANFIS based classifier performs better than neural network based classifier. © 2023 ACM.

关键词： Electrocardiograms

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An Effective Detection of Litchi Disease using Deep Learning 14

An Effective Detection of Litchi Disease using Deep Learning

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Dahiya, Mansi Guru Prasad, M.S. Anand, Tanmay Kumar, Khushi Bansal, Sparsh Naveen Kumar, H.N. Dept. of Computer Science and Engg. Dehradun India Vidyavardhaka College of Engineering Dept. of Electronics and Communication Engg. Karnataka Mysuru India

ISBN: (纸本)9798350335095

Litchi plant diseases are a major threat to global agricultural productivity, economies, and the environment as they cause significant losses. Therefore, it is necessary to have an early and accurate litchi plant monitoring system for farmers, managers, and decision-makers. To develop a constraint-free and reliable work plan for total litchi disease management, a comprehensive review of the literature and industry practices was conducted. A conceptual framework for litchi disease classification was outlined, which uses a structured approach combining professional visual interpretation, pathological analysis, and feature extraction using convolutional neural networks. The diseases in the litchi plant were identified, described, and divided into groups for broad classification. The next step is to recommend a course of treatment for the related litchi plant disease and provide contact information of a pathologist for further queries and suggestions. The aim is to create a user-friendly interface to offer farmers affordable, simple, and quick assistance. © 2023 IEEE.

关键词： Diseases

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Dual Optical Design for VIS-NIR Classification based on Single Pixel and Diffractive Cameras 1

Dual Optical Design for VIS-NIR Classification based on Sing...

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1st IEEE Colombian Caribbean Conference, C3 2023

作者： Jerez, Andres Blanco, Geison Urrea, Sergio Garcia, Hans Castillo, Sergio Arguello, Henry Universidad Industrial de Santander Dept. of Electrical Engineering Bucaramanga Colombia Universidad Industrial de Santander Dept. of Computer Science Bucaramanga Colombia

ISBN: (纸本)9798350341799

Spectral images are used in classification tasks from visible (VIS) and near-infrared (NIR) information of the underlying scene. However, traditional optical architectures that include spectral imaging sensors, require a high economic investment. Then, single pixel cameras (SPCs) with spectrometers have been included in spectral systems because of their low cost. These optical systems allow the acquisition of high-resolution spectral information and low-resolution spatial information. Additionally, diffractive optical cameras (DOCs) based on diffractive optical elements (DOEs) can acquire spectral and spatial information including phase modulation in the wavefront. The DOE is easily able to extract features from a scene for performing computational tasks. Then, this element can be designed from an end-to-end (E2E) optimization approach for classification. Traditional classification approaches have not simultaneously incorporated SPCs and DOCs, ignoring either spatial or spectral features. This work proposes a dual optical architecture for VIS-NIR acquisition in classification tasks: the first branch acquires the spectral information by an SPC, and the second branch acquires the spatial information by a DOC. Specifically, the height map in the DOE and the deep neural network (DNN) parameters are jointly learned from an E2E optimization. The proposed method contains an optical layer that describes the spectral system, a spectral imaging fusion layer that recovers the spatial-spectral information, and a classification neural network that labels the materials over spectral datasets. The proposed method obtained up to 4% in terms of accuracy, precision, recall, and F1 score above traditional optical setups including only CCD cameras. © 2023 IEEE.

关键词： Deep neural networks

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Computing and Analysing PQ Indices for a Consumer with Various Sources of Harmonics and Non-symmetries

Computing and Analysing PQ Indices for a Consumer with Vario...

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2023 Power Quality and Electromagnetic Compatibility at Low-Frequency, PQEMC-LF 2023

作者： Nicolae, Ileana - Diana Nicolae, Petre - Marian Cirstea, Daniel-Nicolae University of Craiova Computer Science and Information Technology Dept. Craiova Romania University of Craiova Electrical Engineering Energetic and Aeronautics Dept. Craiova Romania

ISBN: (纸本)9798350341331

The paper presents a detailed analysis of certain operating regimes that appear for a consumer with various sources of harmonics and non-symmetries. The analyzed waveforms were acquired with a portable dedicated data acquisition system and transferred to a laptop for processing with Fast Fourier Transform (FFT) and Wavelet Packed Transform (WPT). Small differences (FFT vs WPT) were noticed between the computed values of the power quality indices, due to the non-sinusoidal and sometimes non-symmetric nature of the studied regimes and discrete nature of the processed data respectively. The FFT analysis revealed significant non-symmetrical regimes, as great weights for harmonic orders multiple of 3 were found in the three-phase currents waveforms. Reversed flow of active and reactive powers were noticed. A comparative study of the energies produced by current harmonics was made and discussed. A non-symmetry of the consumer as a whole was detected as well. © 2023 IEEE.

关键词： Fast Fourier transforms

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Continual Cell Instance Segmentation of Microscopy Images 48

Continual Cell Instance Segmentation of Microscopy Images

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Chuang, Tzu-Ting Wei, Ting-Yun Hsieh, Yu-Hsing Chen, Chu-Song Yang, Huei-Fang National Sun Yat-sen University Dept. Information Management Taiwan National Taiwan University Dept. Computer Science and Information Engineering Taiwan

ISBN: (纸本)9781728163277

A continual cell instance segmenter aims to continually learn to segment new objects while preserving the ability to localize and distinguish old objects without access to previous data. Besides catastrophic forgetting, background shift, where the background class could contain objects in the old and unseen future classes, could occur. In addition, as acquiring annotations is label-intensive, cell images can be partially labeled. In this paper, we present iMRCNN, which extends Mask R-CNN with knowledge distillation and pseudo labeling, to address these challenges. To preserve the learned skills, the current student distills knowledge from the former teacher at output and feature levels. Furthermore, we employ a pseudo labeling scheme, where the teacher is utilized to identify objects with no labels provided, to deal with background shift and partially labeled data. Experiments on two microscopy image sets demonstrate the effectiveness of iMRCNN over other alternatives in various incremental learning scenarios. © 2023 IEEE.

关键词： Distillation

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Power Quality Problems that Occur at a Company Producing Electrical Equipment

Power Quality Problems that Occur at a Company Producing Ele...

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2023 Power Quality and Electromagnetic Compatibility at Low-Frequency, PQEMC-LF 2023

作者： Nicolae, Petre-Marian Nicolae, Ileana-Diana Nicolae, Marian-Stefan University of Craiova Electrical Engineering Energetic and Aeronautics Dept. Craiova Romania University of Craiova Computer Science and Information Technology Dept. Craiova Romania

ISBN: (纸本)9798350341331

The paper presents the problems that arise when supplying a company producing electrical equipment from the electricity network. The distorting regimes that appear affect the operation of the electric power network, inducing new problems of functional nature. For their study, the authors designed and implemented a data acquisition system in order to acquire, record and transmit data on electrical quantities (three-phase voltages and currents) from the secondary winding of the transformer that supplies the company. Data were transferred to a PC running original software developed by authors, implementing analysis modules based on Fast Fourier Transform and Wavelet Packet Transform. Small differences were revealed between power quality indices computed with both methods. The performed analysis revealed significant distortions of the currents absorbed by the analyzed plant. The total current harmonic distortion and weights of the 5-th harmonic exceeded the limits stated by IEEE Std 519-2022 whilst the value of the power factor was lower than the neutral value, being associated to additional consumptions of power / reactive energy, with effect on the penalties to be paid by the company. © 2023 IEEE.

关键词： Fast Fourier transforms

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