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Swin transformer-based shape-from-focus technique for accurate 3D shape estimation

Optics and Lasers in Engineering 2025年 193卷

作者： Dogan, Ramazan Ozgur Dogan, Hulya Yilmaz, Alper Department of Artificial Intelligence Engineering Faculty of Computer and Information Sciences Trabzon University Trabzon Turkey Department of Software Engineering Faculty of Engineering Karadeniz Technical University Trabzon Turkey Drug and Pharmaceutical Technology Application & Research Center Karadeniz Technical University Trabzon Turkey Photogrammetric Computer Vision Laboratory The Ohio State University Columbus United States

Accurately estimating the three-dimensional (3D) shape of an object from two-dimensional (2D) images is a fundamental challenge in computer vision, with widespread applications in fields such as biomedical imaging and microscopy. Shape-from-Focus (SFF) is a widely adopted technique for addressing this challenge, relying on focus measures from image series captured at varying focal lengths. However, existing SFF techniques often face limitations such as inadequate performance in low-texture regions, sensitivity to noise, and high computational costs when processing high-resolution image series, hindering their effectiveness in real-world applications. To address these limitations, this study proposes a novel SFF technique based on the Swin Transformer, which introduces a hierarchical feature extraction framework and integrates a spatial frequency-based focus function directly into the deep feature space. This enables more robust focus-level detection and improved accuracy in 3D shape estimation for both real and simulated image series. The main contributions include multi-scale attention-based feature modeling and an enhanced sharpness evaluation strategy, yielding superior performance across various data sets. To validate the effectiveness of the proposed technique, extensive experiments are conducted using standard evaluation metrics, complemented by qualitative comparisons via reconstructed 3D shapes. The results consistently demonstrate that the Swin Transformer-based model outperforms existing SFF techniques in both quantitative and visual analyses. These findings highlight the robustness and innovation of the proposed SFF technique, establishing it as a reliable and efficient solution for 3D shape estimation. © 2025 Elsevier Ltd

关键词： Photointerpretation

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Spatial single mode laser source interaction with measured pulse based parabolic index multimode fiber

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Journal of Optical Communications 2024年第0期45卷 s465-s473页

作者： Rashed, Ahmed Nabih Zaki Ahammad, S.K. Hasane Daher, Malek G. Sorathiya, Vishal Siddique, Abrar Asaduzzaman, Sayed Rehana, Hasin Dutta, Nitul Patel, Shobhit K. Nyangaresi, Vincent Omollo Jibon, Rayhan Habib Abdelhamid, Huda Said Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Physics Department Islamic University of Gaza P.O. Box 108 Gaza Palestine Department of Information and Communication Technology Marwadi University Rajkot India Department of Smart Robot Convergence and Application Engineering Pukyong National University Busan48513 Korea Republic of Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Computer Sc and Engg. Dept. SRM University Andhra Pradesh Guntur India Electronics and Communication Engg. Department Marwadi University Gujarat Rajkot India Tom Mboya University College P.O. Box 199-40300 Homabay Kenya Electronics and Communication Engineering Discipline Khulna University Khulna9208 Bangladesh

The study clarified spatial single mode laser interaction with measured pulse based parabolic index multimode fiber. Peak power level margin, maximum/minimum signal amplitude margin after parabolic index multimode fiber are measured with core radius of 25 μm, cladding thickness of 10 μm, refractive index peak of 1.4142, length of 300 m, and refractive index step of 1%. Maximum signal power margin against spectral frequency after PIN light detector based parabolic fiber properties is tested under the same operating parameters. The signal power amplitude/power within parabolic index multimode fiber is also measured based on variations of fiber lengths and relative refractive index step. The study implies the multimode graded index fibers with parabolic or near parabolic index profile cores have transmission bandwidths than other multimode fibers. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Multimode fibers

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Signal propagation parameters estimation through designed multi layer fibre with higher dominant modes using OptiFibre simulation

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Journal of Optical Communications 2024年第0期45卷 s453-s463页

作者： Zaki Rashed, Ahmed Nabih Ahammad, S.K. Hasane Daher, Malek G. Sorathiya, Vishal Siddique, Abrar Asaduzzaman, Sayed Rehana, Hasin Dutta, Nitul Patel, Shobhit K. Nyangaresi, Vincent Omollo Jibon, Rayhan Habib Ibrahim, Anas Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Physics Department Islamic University of Gaza P.O. Box 108 Gaza Palestine Department of Information and Communication Technology Marwadi University Rajkot India Department of Smart Robot Convergence and Application Engineering Pukyong National University Busan48513 Korea Republic of Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Computer Science and Engineering Department SRM University Andhra Pradesh Guntur India Electronics and Communication Engineering Department Marwadi University Gujarat Rajkot India Tom Mboya University College P.O. Box 199-40300 Homabay Kenya Electronics and Communication Engineering Discipline Khulna University Khulna9208 Bangladesh

The aim and scope of the paper is to simulate the signal propagation parameters estimation through designed multi-layer fibre with higher dominant modes by using OptiFibre simulation software. The multi-layer fibre profile has a length of 1000 m is designed and clarified with six layers. RI difference profile variations are clarified with radial distance variations. Modal/group index, group delay, dispersion, mode field diameter and total fibre losses are demonstrated with the fibre wavelength variations. All the dominant mode field distribution for multi-layer fibre are simulated and demonstrated. The other modes for designed multi-layer fibre with the theoretical fibre cutoff values for the different modes based the designed multi-layer fibre are analyzed and clarified clearly in details. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Parameter estimation

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Semi-Supervised and Self-Supervised Collaborative Learning for Prostate 3D MR Image Segmentation

Semi-Supervised and Self-Supervised Collaborative Learning f...

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IEEE International Symposium on Biomedical Imaging

作者： Yousuf Babiker M. Osman Cheng Li Weijian Huang Nazik Elsayed Leslie Ying Hairong Zheng Shanshan Wang Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China Faculty of Mathematical and Computer Sciences University of Gezira Wad Madani Sudan Department of Biomedical Engineering and Department of Electrical Engineering University at Buffalo The State University of New York New York USA Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong China

Volumetric magnetic resonance (MR) image segmentation plays an important role in many clinical applications. Deep learning (DL) has recently achieved state-of-the-art or even human-level performance on various image segmentation tasks. Nevertheless, manually annotating volumetric MR images for DL model training is labor-exhaustive and time-consuming. In this work, we aim to train a semi-supervised and self-supervised collaborative learning framework for prostate 3D MR image segmentation while using extremely sparse annotations, for which the ground truth annotations are provided for just the central slice of each volumetric MR image. Specifically, semi-supervised learning and self-supervised learning methods are used to generate two independent sets of pseudo labels. These pseudo labels are then fused by the Boolean operation to extract a more confident pseudo label set. The images with either manual or network self-generated labels are then employed to train a segmentation model for target volume extraction. Experimental results on a publicly available prostate MR image dataset demonstrate that, while requiring significantly less annotation effort, our framework generates very encouraging segmentation results. The proposed framework is very useful in clinical applications when training data with dense annotations are difficult to obtain.

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Three-Dimensional Reconstruction of Moving Hdr Object Based on Psp

SSRN

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SSRN 2022年

作者： Wu, Ke Xie, Yinao Lu, Lei Yin, Yongkai Xi, Jiangtao Faculty of Artificial Intelligence in Education Central China Normal University Wuhan430079 China College of Information Science and Engineering Henan University of Technology Zhengzhou450001 China Shandong Provincial Key Laboratory of Laser Technology and Application Department of Optics School of Information Science and Engineering Shandong University Jinan250100 China School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW2522 Australia

High quality 3D reconstruction of HDR object can be achieved by projecting extra fringe patterns with different intensity. However, it requires the object to be kept static. The object motion not only introduces phase shift among the fringe patterns, but also changes the position of the overexposure pixels. This paper proposes a new method to reconstruct the moving HDR object by utilizing the features of motion. For the specific point on the object, overexposure will not happen among all the fringe patterns as the overexposure position is changed with the motion. The unsaturation fringe patterns are selected from the captured fringe patterns and the correct phase information is retrieved based on unequal phase shift algorithm. The effectiveness of the proposed algorithm is verified by the experiments. © 2022, The Authors. All rights reserved.

关键词： Interferometry

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Decomposed Neural Architecture Search for image denoising

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Applied Soft Computing 2022年 124卷

作者： Li, Di Bai, Yunpeng Bai, Zongwen Li, Ying Shang, Changjing Shen, Qiang School of Computer Science National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Provincial Key Laboratory of Speech & Image Information Processing Northwestern Polytechnical University Xi'an710129 China Department of Computer Science Faculty of Business and Physical Sciences Aberystwyth University AberystwythSY233DB United Kingdom Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data School of Physics and Electronic Information Yan'an University Yan'an716000 China

In practical applications of deep learning, as the demand for the modeling capability increases, the network size may need to be massively enlarged in response. This may form a significant challenge in practice, especially when facing the dilemma of limited computational resources, making model compression indispensable. It can be time-consuming and interminable to obtain an appropriate network architecture through manual compression. In this paper, we propose an automated method for searching decomposed network architectures, named DNAS (standing for Decomposed Neural Architecture Search). It integrates both tasks of neural architecture search and tensor decomposition based model compression within a unified framework. The method is able to efficiently find a compact network with high performance for image denoising, with respect to memory and runtime. Particularly, using one single V100 GPU, it only takes about 1.5 h to obtain a denoising network on the BSD500 dataset. Experimental results demonstrate that compared with models developed using existing methods, DNAS consumes significantly less inference time and employs much fewer trainable parameters, outperforming existing approaches on both synthetic and real-world denoising datasets. © 2022 Elsevier B.V.

关键词： Network architecture

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Multi Model Implementation on General Medicine Prediction with Quantum Neural Networks

Multi Model Implementation on General Medicine Prediction wi...

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Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), International Conference on

作者： Swarn Avinash Kumar Abhishek Kumar Vishal Dutt Rashmi Agrawal IIIT Allahabad UP India Chitkara University Institute of Engineering and Technology Chitkara University Himachal Pradesh India Aryabhatta College Ajmer India Faculty of Computer Application Manav Rachna International Institute of Research and Studies Faridabad India

ISBN: (数字)9781665419604

ISBN: (纸本)9781665429986

Medical is the large-scale repository where there is more chances to create a new model in the zone of prediction. The proposed methodology mentioned in this article speaks about the general medicine prediction using QNN which is a challenging factor in the prediction model design and implementation. The main cause of predicting the general medicine is to predict the accurate medical combination for the patient who needs some medication and doesn't find the accurate medication in pharmacy or with the druggist. The proposed methodology with QNN is having the option to predict the accurate general medicine for the patient with some disease factors as the symptoms. The accuracy achieved is 92% with the neural network which is a hybrid mechanism with the initial data factors are considered using the expert systems. The concept of expert systems is required in this mechanism because frames are being used in this proposed architecture related to the medicine prediction. Using frames, we can make the combination of the drugs and predict the accurate mechanism to check the alternate general medicine which is no harm to the patient until he or she gets the medical support. This general medicine prediction will be the standby process for the patient who requires the medication immediately and not able to get the accurate medicines from the nearest pharmacy.

关键词： Drugs Neural networks Predictive models Communications technology Expert systems Diseases

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Correction to: Image-Based Sentiment Analysis Using InceptionV3 Transfer Learning Approach

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SN computer Science 2023年第4期4卷 1-1页

作者： Meena, Gaurav Mohbey, Krishna Kumar Kumar, Sunil Chawda, Rahul Kumar Gaikwad, Sandeep V. Department of Computer Science Central University of Rajasthan Ajmer India School of Business Woxsen University Hyderabad India Department of Computer Science Assam University Silchar India Faculty of Computer Science and Application SMPICA Charotar University of Science and Technology Anand India

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Super Twisting Sliding Mode Control Strategy for a Three-Level T-Type Dual MPPT Inverter

Super Twisting Sliding Mode Control Strategy for a Three-Lev...

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Compatibility in Power Electronics (CPE)

作者： Farzaneh Bagheri Naki Guler Marco Rivera Hasan Komurcugil Department of Electrical and Electronic Engineering Antalya Bilim University Antalya Turkey Electrical and Electronic Engineering Technology Faculty Gazi University Ankara Turkey Renewable Energy and Smart Grids Application and Research Center Gazi University Ankara Turkey Power Electronics Machines and Control (PEMC) Research Institute University of Nottingham Nottingham UK Laboratorio de Conversión de Energías y Electrónica de Potencia (LCEEP) Vicerrectoría Académica Universidad de Talca Curicó Chile Department of Computer Engineering Eastern Mediterranean University (EMU) Famagusta Turkey

ISBN: (数字)9798331515171

ISBN: (纸本)9798331515188

Nowadays Residential and small commercial power systems are taking advantage of the dual maximum power point tracking (MPPT) inverters, optimizing energy harvesting from two individual solar panel arrays to increase performance and energy output. Three-level T-type inverters are also famous due to their lower total harmonic distortion, high efficacy, and lower voltage stress on the switch which are a good option to be integrated into the dual MPPT solar plants. So, this article incorporates the dual MPPT solar plants with a T-Type grid-connected inverter which uses a double super twisting sliding mode control (STSMC) to control the injected currents to the grid in d and q reference frames. The STSMC mitigates chattering while showing robustness under model variations and dynamic response. The efficiency of the proposed control method under different irradiation values is verified through simulation results.

关键词： Maximum power point trackers Total harmonic distortion Switches Inverters Robustness Real-time systems Solar panels Time factors Voltage control Sliding mode control

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Extremely Large-Scale Dynamic Metasurface Antennas (XL-DMAs): Near-Field Modeling and Channel Estimation

arXiv

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arXiv 2024年

作者： Yang, Songjie Lyu, Wanting Ning, Boyu Xiu, Yue Xiong, Youzhi Chen, Hua Assi, Chadi Yuen, Chau The National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China College of Air Traffic Management Civil Aviation Flight University of China Sichuan618311 China College of Physics and Electronic Engineering Sichuan Normal University Chengdu610101 China The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China The Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo315211 China Concordia University MontrealQCH3G 1M8 Canada The School of Electrical and Electronics Engineering Nanyang Technological University Singapore

Dynamic metasurface antennas (DMAs) represent a novel transceiver array architecture for extremely large-scale (XL) communications, offering the advantages of reduced power consumption and lower hardware costs compared to conventional arrays. This paper focuses on near-field channel estimation for XL-DMAs. We begin by analyzing the near-field characteristics of uniform planar arrays (UPAs) and introducing the Oblong Approx. model. This model decouples elevation-azimuth (EL-AZ) parameters for XL-DMAs, providing an effective means to characterize the near-field effect. It offers simpler mathematical expressions than the second-order Taylor expansion model, all while maintaining negligible model errors for oblong-shaped arrays. Building on the Oblong Approx. model, we propose an EL-AZ-decoupled estimation framework that involves near- and far-field parameter estimation for AZ/EL and EL/AZ directions, respectively. The former is formulated as a distributed compressive sensing problem, addressed using the proposed off-grid distributed orthogonal least squares algorithm, while the latter involves a straightforward parallelizable search. Crucially, we illustrate the viability of decoupled EL-AZ estimation for near-field UPAs, exhibiting commendable performance and linear complexity correlated with the number of metasurface elements. Moreover, we design an measurement matrix optimization method with the Lorentzian constraint on DMAs and highlight the estimation performance degradation resulting from this constraint. Copyright © 2024, The Authors. All rights reserved.

关键词： Channel estimation

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