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1st international conference on Advances in signal processing and Communication Engineering, ICASPACE 2021

1st International Conference on Advances in Signal Processin...

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1st international conference on Advances in signal processing and Communication Engineering, ICASPACE 2021

ISBN: (纸本)9789811955495

The proceedings contain 44 papers. The special focus in this conference is on Advances in signal processing and Communication Engineering. The topics include: Single-Precision Floating-Point Multiplier Design Using Quantum-Dot Cellular Automata with Power Dissipation Analysis;compression Techniques for Low Power Hardware Accelerator Design: Case Studies;sequence Set Design for Radar System;design of an All Digital Phase-Locked Loop Using Cordic Algorithm;analysis of Deep Learning algorithms for image Denoising;an Extensive Survey on Assessment of Multicore Processors for Embedded Systems;image Segmentation Techniques and Optimization algorithms for Lung Cancer Detection;handwritten to Text Document Converter;An Efficient Energy Aware for Reliable Route Discovery Using Energy with Movement Detection Technique in MANET;Lumped Circuit Modeling at Nanoscale (Part-II: Coupling Between Two Nanospheres);design and Implementation of Imprecise Adders for Low-Power Applications;speech Processed Public Addressing System;an Approach Towards Data Privacy Issues in Distributed Cyber Physical System;Classification of LPI Radar signals Using Multilayer Perceptron (MLP) Neural Networks;a Systematic Review on Screening of Diabetic Retinopathy and Maculopathy Using Artificial Intelligence;Area Efficient and High-Throughput Radix-4 1024-Point FFT Processor for DSP Applications;air Quality Monitoring System Based on Artificial Intelligence;an Improved Technique for Identification of Forgery image Detection Using Clustering Method;EEG signal Analysis During Stroop Task for Checking the Effect of Sleep Deprivation;UWB Localization Procedures with Range Control Methods—A Review;deep Learning Model for Multiclass Classification of Diabetic Retinal Fundus images Using Gradient Descent Optimization;multilevel Authentication to Wireless Sensor Networks Against Malicious Attacks Using Butterfly Method.

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Multi-threshold laser stripe image segmentation based on improved black widow algorithm

Multi-threshold laser stripe image segmentation based on imp...

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2023 international conference on image, signal processing, and Pattern Recognition, ISPP 2023

作者： Xu, Jinli Liu, Tianyu Lu, Jie School of Electrical and Mechanical Engineering Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781510666351

To solve the problems of low segmentation accuracy, mis-segmentation, and exponential increase of computation time with the rise of the number of thresholds when multi-threshold image segmentation is performed on images of multiple laser stripes in the structured lights windshield assembly detection environment, an improved black widow optimization algorithm (IBWOA) for multi-threshold laser stripe image segmentation is proposed. In the population initialization stage, Logistic chaotic mapping is used to enhance the initial population randomness. In the position updating stage, an adaptive step size strategy is introduced to improve the search speed and accuracy in the later stage, and individual variation based on the reverse learning strategy is introduced to avoid falling into local optimal solutions. Compared with existing swarm intelligence optimization algorithms, the results show that IBWOA has better search speed, accuracy, and escape ability to jump out of locally optimal solutions in multi-threshold laser stripe image segmentation. © 2023 SPIE.

关键词： image segmentation

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Unsupervised image Segmentation model based on W Net architecture and Conditional Random Field for Underwater images 7

Unsupervised Image Segmentation model based on W Net archite...

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7th international conference on advanced Computing and Communication Systems, ICACCS 2021

作者： Saleh, Esra Sorkty Mithun Haridas, T.P. Supriya, M.H. Cochin University of Science and Technology Department of Electronics Kochi India

ISBN: (纸本)9781665405201

Under water imaging has been extensively used in monitoring the marine ecosystems for quite some time. The automated learning systems that are much explored in marine ecosystem are mainly supervised methods. Supervised methods even though require less human intervention, still demands considerable manual effort for the careful design of the dataset. The large amount of labelled and annotated data needed for proper learning, as well as the attention required for designing the ground truth dataset for efficient training, makes the supervised learning approach less attractive, especially in the underwater scenarios. This work explores the possibility of unsupervised learning methods for the analysis of the underwater images using segmentation algorithms, which does not need ground truth annotations and is much more scalable. images and videos from Fish4Knowledge database is utilized for this work to train the unsupervised architecture based on W-Net architecture. The autoencoder architecture is analyzed considering the segmented output from the first half and reconstructed image from the second half using soft N-cut loss and reconstruction loss respectively. Post processing method of Conditional Random Field is also applied for smoothing the initial segmentation. The performance is analyzed using the learning curves and the metrics such as VI, PRI and SC. © 2021 IEEE.

关键词： Random processes

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Providing a desired quality of BPG compressed images for FSiM metric 3

Providing a desired quality of BPG compressed images for FSi...

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3rd IEEE international conference on advanced Trends in Information Theory, ATIT 2021

作者： Li, Fangfang Lukin, Vladimir Okarma, Krzysztof Fu, Yanjun Dept. of information-Communication Technologies National Aerospace University – KhAi Kharkiv Ukraine Nanchang Hangkong University Nanchang China Dept. of Signal Processing and Multimedia Engineering West Pomeranian University of Technology in Szczecion Szcaecin Poland

ISBN: (纸本)9781665438452

it is a common task in image lossy compression to provide a reasonable trade-off between a desired compression ratio (as large as possible) and an appropriate (preset according to a chosen metric) quality. Recently, a Better Portable Graphics (BPG) coder has been proposed that might become a new standard. A quality parameter Q is used in it to vary image quality and compression ratio. However, a given Q for particular images to be compressed produces quite different compression ratios and quality measured by a given quality metric. To provide a given quality of compressed images characterized by a visual quality metric FSiMc, we propose and analyze a two-step algorithm based on preliminary obtained average rate/distortion curve and its linear approximation. For this algorithm, the second step that calculates the improved estimate of Q and employs it for final compression allows decreasing variance of the produced FSiMc by about one order of magnitude compared to the first compression step where Q is set according to the average rate-distortion curve. The algorithm is applied for a wide set of desired values of FSiMc. it is also tested for a set of images not used in obtaining the average rate/distortion curve. © 2021 iEEE.

关键词： image compression

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2021 IEEE 8th Uttar Pradesh Section international conference on Electrical, Electronics and Computer Engineering, UPCON 2021

2021 IEEE 8th Uttar Pradesh Section International Conference...

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8th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and Computer Engineering, UPCON 2021

ISBN: (纸本)9781665409629

The proceedings contain 110 papers. The topics discussed include: a bottom-up approach applied to dependency parsing in Malayalam language;probabilistic modeling of human locomotion for biped robot trajectory generation;expert monitoring system for online sessions employing ResNet;multimodal meme sentiment analysis with image inpainting;advanced signal processing based condition monitoring of PMSM for stator-inter turn fault;coordinate-assisted routing in a biomedical sensor network with schedule-based dynamic sink;a review of neural machine translation based on deep learning techniques;and computation of secrecy and outages for hybrid FSO/RF system with modified switching.

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OCT image processing System For Numerical Simulation of Fundus Temperature Distribution

OCT Image Processing System For Numerical Simulation of Fund...

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18th international Scientific and Technical conference on Optical Technologies for Communications

作者： Shirokanev, Alexander S. Ilyasova, Nataly Yu Andriyanov, Nikita A. Demin, Nikita S. Samara Natl Res Univ Moskovskoye Shosse 34 Samara 443086 Russia IPSI RAS Branch FSRC Crystallog & Photon RAS Molodogvardeyskaya 151 Samara 443001 Russia Financial Univ Govt Russian Federat Leningradskiy Av 49 Moscow 125167 Russia

ISBN: (数字)9781510644250

ISBN: (纸本)9781510644250

The safety of laser coagulation in the treatment of diabetic retinopathy depends on the correct selection of laser exposure parameters. In this paper, it was proposed to use technology for numerical modeling of the temperature distribution in the fundus based on its structure formed from optical coherence tomography (OCT) images. For such a formation, it is required to process each image and then interpolate the three-dimensional surfaces. Further, the formed structure is used for numerical simulation. This approach will potentially allow automating the extremely time-consuming procedure for choosing a coagulate placement plan. The paper considers algorithms that improve performance when solving the problem of mathematical modeling using the maximum load of CPU and GPU devices, i.e. parallel and high-performance algorithms.

关键词： mathematical modeling image processing digital signal processing laser coagulation retinopathy high-performance algorithms

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MDIFNet: Multiscale distant information fusion network for thyroid segmentation in 3D ultrasound image 21

MDIFNet: Multiscale distant information fusion network for t...

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6th international conference on Multimedia Systems and signal processing, ICMSSP 2021

作者： Feng, Chen Yin, Tinghui Song, Hong Tang, Songyuan Yang, Jian Laboratory of Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and Photonics Beijing Institute of Technology China Imaging Third Affiliated Hospital of Sun Yat-Sen University China School of Computer Science and Technology Beijing Institute of Technology China

ISBN: (纸本)9781450390378

The thyroid segmentation in 3D ultrasound image can provide necessary volumetric information in diagnosis and treatment. Clinically, 3D thyroid US images are usually stacks of 2D frames acquired by freehand scanning, which results in good performance of 2D segmentation methods. However, thyroid nodules cause difficulty to these algorithms because of strong anisotropy, whereas current approaches are mostly for healthy thyroid images. This paper proposes a multiscale distant information fusion network to segment clinical thyroid images with nodules. Our fully convolutional network consists of the following: (1) deep supervision of normalized boundary distance map, (2) multi-scale fusion module combined with attention mechanism, and (3) dense dilated refinement module to refine segmentation probability in a multi-scale way. We conducted ablation study and cross-validation on clinical dataset provided by The Third Affiliated Hospital of Sun Yat-Sen University and obtained the best dice result of 0.9070. Notably, our method also outperformed other methods on ultrasonography dataset and obtained a dice score of 0.93. © 2021 ACM.

关键词： Ultrasonics

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Digital image restoration using modified richardson-lucy deconvolution algorithm

Digital image restoration using modified richardson-lucy dec...

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international conference on image processing and Capsule Networks, ICIPCN 2020

作者： Jency Rubia, J. Babitha Lincy, R. Department of Electronics and Communication Engineering Sri Venkateswara College of Engineering Sriperumbudur602 117 India

ISBN: (纸本)9783030518585

Since the Surveillance camera came into the market, the advanced digital image processing is getting more research importance. One of the major issues of digital photographing is motion and image blur. This can be occurring when the camera is in motion, the shape of the blurring is constant, but only the spatial extent is varying. Here, a novel algorithm is proposed for deconvoluting the image samples in the filtering process. Moreover, the proposed algorithm is successfully useful for compressed domain operations such as downsampling, translation, and filtering, etc. The recommended deconvolution algorithm produces the approximated output images that are perceptually closer to the actual image with reduced computational complexity. In this paper, the proposed multiplier less convolution algorithm is employed in the Richardson-Lucy filter for the Deblurring analysis. Also, this proposed method was compared with the existing techniques and stated that the novel multiplier less deconvolution algorithm provides better performance in terms of PSNR. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Approximation algorithms

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Design and implementation of personal online disk system based on DBN image recognition algorithm 3

Design and implementation of personal online disk system bas...

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3rd international conference on signal image processing and Communication, ICSIPC 2023

作者： Wen, Mingxing Chen, Tongfei Tang, Wenyang Chen, Elaine Pan, Zhihong School of Information and Intelligent Engineering Guangzhou Xinhua University Guangzhou China School of Art Media Guangzhou Xinhua University Guangzhou China

ISBN: (纸本)9781510670945

With the growth of the Internet and the age of information explosion, more and more people need network drives to store and share the resources they find online. While downloading files to a local hard drive can ensure data security, this also brings with it many inconveniences, such as the need to share with others using third-party websites or communication software, or the need to transfer files using a removable hard drive. As a result, personal network drives have emerged on the market to make data sharing easier by transferring files to a server. This project will retain the basic functions of a traditional network drive system, such as file uploading, downloading, and deletion, while taking into account the security of the data and using deep learning-based DBN algorithms for image recognition, using artificial intelligence and image recognition techniques to detect pirated and illegal image material. Through the combined application of the above technologies, an efficient personal web-disk system is designed and implemented. © 2023 SPIE.

关键词： image recognition

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Fast architecture for low level vision and image enhancement for reconfigurable platform 1

Fast architecture for low level vision and image enhancement...

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1st IEEE international conference on Advances in Electrical, Computing, Communications and Sustainable Technologies, ICAECT 2021

作者： Narasimhamurthy, Chiranjeevi Gubbi Kulkarni, Subhash Bangalore India

ISBN: (纸本)9781728157900

image processing architecture and algorithms are used for the purpose of improving the image quality and to extract complete information in more precise manner. The need to process in real time has led to implement them on the target device with real time constraints like power and area. To implement image processing algorithms and architecture with the help of high level languages needs more blocks of code apart from inefficient in terms of time constraint. The easiest way to deal with facilitating usage of Xilinx System Generator/XSG blocks, XSG is a tool where we can build our design using pre existing block level components which are captured by using Xilinx block set from library environment and implement as per user requirement. The main responsibility of system generator is Xilinx block sets that provides the package integration with MATLAB Simulink and helps in co- simulating FPGA hardware module. As per part application category, edge detection is a major essential application in medical field for proper diagnosis and correct treatments. Field-Programmable Gate Arrays (FPGAs) have become more popular computing platforms as target device for digital signal processing. The Zynq System on Chip (SOC) is a dual-processor platform with shared memory. This paper describes a fast architecture implementation of Sobel edge detection using the Zynq as a reconfigurable device. Our implementation is to merge both software and hardware using the Vivado and Zynq (SoC). As a result, our implementation is fast in terms of performance compare to the pre existing models. We make a comparison with other conventional edge detection techniques and show that the speed of operation of this design is much faster. This approach is tested over hardware or different gradient test vectors. Finally the algorithms are evaluated for the major essential images from the medical field to extract lasting effect in detecting the edges using gradient factor. The area and power factors are evalu

关键词： Simulink

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