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检索条件"任意字段=2nd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2022"

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Computer simulation and prediction of coordination capture of Pb2+and Hg2+by the Salophen 3

Computer simulation and prediction of coordination capture o...

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3rd international conference on advanced algorithms and signal image processing, aasip 2023

作者： Duan, Shuangni Ling, Ming Lan, Wenbo Zhou, Feng Deng, Chao Xiong, Junhui Liu, Zhijuan Zeng, Can School of Public Health Xiangnan University Hunan Chenzhou423000 China Chenzhou City Heavy Metal Poll. Health Risk Assessment Technology Research and Development Center Hunan Chenzhou423000 China The Second People's Hospital of Chenzhou Hunan Chenzhou423000 China Affiliated Hospital of Xiangnan University Chenzhou Hunan423000 China University of South China Hengyang Hunan421000 China

ISBN: (纸本)9781510668522

This study used Gauss 16 computing software based on the computational methods of density functional theory (DFT) to simulate and compare the Salophen-Cd and Salophen-Hg complexes. The structural parameters, infrared vibrational, ultraviolet absorption spectra and coordination binding energies of the Salophen ligand with Cd2+ and Hg were analyzed and compared. The results showed that Salophen can form stable complexes with Cd2+ and Hg2+, which can be qualitatively distinguished by their characteristic infrared vibrational spectra and ultraviolet absorption peak values. Importantly, Salophen showed a significantly higher capture ability for Cd than for Hg, suggesting its potential application in the selective capture of Cd2+. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Mercury compounds

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Design of Machine Vision image Target Recognition System Based on Improved ORB Algorithm

Design of Machine Vision Image Target Recognition System Bas...

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Mobile Networks and Wireless Communications (ICMNWC), IEEE international conference on

作者： Beiyuan Liang Guangxi Vocational&Technical Institute of Industry Nanning Guangxi China

ISBN: (纸本)9781665491129

With the rapid development of computer technology and the Internet era, machine vision is a new science and technology formed by the cross-integration of various disciplines such as image processing theory, advanced information science and digital signal processing methods based on computers. The application of computer in information processing has become an inevitable trend, it can better acquire and understand images, and it can quickly and effectively analyze, extract useful targets and provide decision makers with the required content. This can also improve work efficiency and accuracy to achieve a more precise and automated management level, and play a huge role in life. First of all, this paper uses the ORB algorithm for target recognition for the identification and positioning of static targets, but this algorithm still has the problem of low feature matching accuracy. Therefore, an improved ORB feature matching method based on multiple constraints is proposed; Secondly, it studies the design of the machine vision image target recognition system, including the overall function design of the system, the system process design and the system experimental verification.

关键词： Wireless communication Process design Information science Target recognition Machine vision signal processing algorithms Digital signal processing

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advanced directionally weighted demosaicing for digital cameras

Advanced directionally weighted demosaicing for digital came...

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international conference on signal processing and Communication Systems, ICSPCS

作者： Tae-young Jung Siyoung Yang Joohyun Lee Jechang Jeong Department of Electronics and Computer Engineering Hanyang University Seoul South Korea

Most digital camera uses the color filter array to reduce the cost and size. When we use the color filter array, however, we need to interpolate the missing color components. In this paper, we propose an advanced directionally weighted demosaicing algorithm for the color filtered images of the single-sensor digital camera. The proposed algorithm estimates the missing pixels by summing weighted color-differences in various directions. Compared to the conventional algorithms, the proposed algorithm achieves better visual quality without visual artifacts, such as aliasing and zippering.

关键词： Digital cameras Interpolation Digital filters Costs image edge detection Color Humans Visual system image reconstruction

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On the Role of Perceptual Information in image Classification 1

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2nd international conference on signal and Data processing, ICSDP 2022

作者： Kashyap, Manish Department of Electronics and Communication Engineering National Institute of Technology Bhopal India

ISBN: (数字)9789819914104

ISBN: (纸本)9789819914098

In this paper, the following hypothesis is validated—"Alternate image representations, of the same image, that preserve visual perception do not degrade the classification accuracy". The underlying phenomenon that is exploited is the property of the human visual system to see an area in a digital image as a continuous region even though it is discrete. This is because the human eye senses energy per unit area rather than closely spaced individual pixels. In our current work, we use ‘Linear discriminant analysis’ (LDA) and ‘Convolutional neural networks’ (CNN) for classifying images and their alternate representations. The results suggest that the representation of data is immaterial and perceptual information actually classifies the images. The primary contribution of this paper is suggesting ‘feature space reduction while preserving perception’ as an alternative to ‘dimensionality reduction’. By using traditional methods of dimensionality reduction, perception-based information is lost. In the process, we develop the following: (1) An algorithm to convert 256 Gy level grayscale image to gray level grayscale image where such that the visual perception is preserved. The case of, i.e., binary image is particularly of interest to us because of its appealing applications. (2) An algorithm to define clustering efficiency based on density. The applications of reduced data size and search space include compression, transmission efficiency, big data handling, efficient storage, etc. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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Improvement of satellite image classification: Approach based on Hadoop/MapReduce

Improvement of satellite image classification: Approach base...

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international conference on advanced Technologies for signal and image processing (ATSIP)

作者： I. Chebbi W. Boulila I. R. Farah Riadi Laboratory National School of Computer Science Manouba University Tunisia

ISBN: (纸本)9781467385275

The revolution of technologies (social networks, smartphones, GPS and Remote Sensing image) increase the volume of informations wich makes humanity in new need “Storage of huge volume of data”. the traditional strategy to store data become problem for humanity and then this need build new art to resolve this problems the “Spatial Big Data (SBD)” SBD store proncipally three types of data:vector data, raster data and network data. The complexity and nature of spatial databases make them ideal for applying parallel processing. This also emphasizes the need for developing new efficient geospatial analytic for analyzing spatial big data. So, we review the most used spatial data algorithms attracting human interests especially when the amount of satellite images continues to grow as more information becomes available. In this context, we propose a system based on Hadoop an open source system that implements the MapReduce programming model and that can improve the classification of large scale remote sensing image and benefit the power of spatial big data concept.

关键词： Spatial databases Remote sensing Satellites Big data image segmentation Geographic information systems Vegetation mapping

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Removal of Specular Reflections in Tooth Color image by Perceptron Neural Nets

Removal of Specular Reflections in Tooth Color Image by Perc...

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2010 2nd international conference on signal processing System(2010年信号处理系统国际会议 ICSPS 2010)

作者： Seong-Taek Lee Tae-Ho Yoon Kyeong-Seop Kim Wonse Park Kee-Deog Kim School of Biomedical Engineering Konkuk University Chungju Korea School of BiomedicalEngineering Konkuk University Chungju Korea Department of Advanced General Dentistry Yonsei University Seoul Korea

This study presents the removal algorithm of specular reflections in a tooth color image to eliminate the specularities which degrades the performance of color image segmentation algorithms. Our proposed methodology includes two tasks: (i) automated detection of specular reflections by Perceptron neural nets and (ii) recursive corrections of the specularities by applying a smoothing spatial filter on the target pixels (specular regions) based on the decision of Perceptron.

关键词： Specular reflections Perceptron neural nets Tooth Color image

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-ADMM Algorithm for Sparse image Recovery Under Impulsive Noise 2nd

-ADMM Algorithm for Sparse Image Recovery Under Impulsive No...

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2nd EAI international conference on advanced Hybrid Information processing, ADHIP 2018

作者： Hao, Dongbin Zhang, Chunjie Hao, Yingjun College of Information and Communication Engineering Harbin Engineering University HarbinHeilongjiang150001 China

ISBN: (纸本)9783030190859

The existing compressive sensing recovery algorithm has the problems of poor robustness, low peak signal-to-noise ratio (PSNR) and low applicability in images inpainting polluted by impulsive noise. In this paper, we proposed a robust algorithm for image recovery in the background of impulsive noise, called -ADMM algorithm. The proposed algorithm uses -norm substitute -norm residual term of cost function model to gain more image inpainting capability corrupted by impulsive noise and uses generalized non-convex penalty terms to ensure sparsity. The residual term of -norm is less sensitive to outliers in the observations than -norm. And using the non-convex penalty function can solve the offset problem of the -norm (not differential at zero point), so more accurate recovery can be obtained. The augmented Lagrange method is used to transform the constrained objective function model into an unconstrained model. Meanwhile, the alternating direction method can effectively improve the efficiently of -ADMM algorithm. Through numerical simulation results show that the proposed algorithm has better image inpainting performance in impulse noise environment by comparing with some state-of-the-art robust algorithms. Meanwhile, the proposed algorithm has flexible scalability for large-scale problem, which has better advantages for image progressing. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Compressed sensing

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A Smart Device for Automatic Detection of Lane-Marking on the Roads Using image processing 2nd

A Smart Device for Automatic Detection of Lane-Marking on th...

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2nd international conference on signal and Data processing, ICSDP 2022

作者： Suman, Preetam Suman, Amrit Jaiswal, Varshali Vellore Institute of Technology Bhopal India Sharda University Greater Noida India

ISBN: (纸本)9789819914098

Travelling by roads is the most common and oldest way to reach the destination. The fast speed vehicles are growing each day. Many automobile industries are working on development of fast speed vehicle with various security features. Security features include safety air bags, safety breaks, and many electronic supports. But still due to various reasons vehicle crashes and road accidents happen every day. Road accidents cause loss of infrastructure and monitory. These results a lot of injuries and deaths every year in every city. Government has lot of road safety protocols, rules, and regulations to prevent road accidents. Every year government is spending a lot for road safety. This paper is presenting a smart device with various safety features. The device can be mounted in any four wheeler vehicle and can make an ordinary vehicle to semi-smart vehicle. The device is featured with monitoring of engine, tires, and other peripherals. This paper is focused on lane marking and obstacle detection on the roads. For the lane marking detection improved Hough transform, Canny edge detector has been used. And for the obstacle detection, improved CNN has been used. The algorithms are implemented on hardware and tested on real objects by mounting the device on vehicle. The developed algorithms are efficient, and results are promising. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Object detection

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Automatic tracking intelligent car based on image processing

Automatic tracking intelligent car based on image processing

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signal processing, Communications and Engineering Management conference (ISPCEM), international

作者： Chenting Zhao Department of Electrical Engineering North China Electric Power University Baoding China

Abstarct-N ow the car has become an essential tool for people to travel, but driving a car is still a skill. The safety and reliability of automobile driving also has a great relationship with the driver's state. In addition, because of the incomplete controllability of man-made driving route and speed, traffic congestion has become an important problem in cities. It is imperative to solve these problems by means of science and technology, and driverless technology has emerged as the times require. The automatic-tracking smart car we study is an attempt to study driverless technology. In this car, gray-scale camera is used as the main sensor, and gyroscope is used as the auxiliary sensor, and PID algorithm is used to realize automatic tracking and special element recognition.

关键词： Urban areas signal processing algorithms Pulse width modulation signal processing Cameras Safety Gyroscopes

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An optimized hardware architecture of 4×4, 8×8, 16×16 and 32×32 inverse transform for HEVC

An optimized hardware architecture of 4×4, 8×8, 16×16 and...

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international conference on advanced Technologies for signal and image processing (ATSIP)

作者： Manel Kammoun Emna Maamouri Ahmed Ben Atitallah Nouri Masmoudi LETI laboratory—ENIS University of Sfax Sfax TUNISIA

ISBN: (纸本)9781467385275

Most video coding standards use transform algorithms to reduce the size of data characterizing a video signal. The traditional transform matrices as in H.264 are limited to 4×4 and 8×8 sizes. However, the flexibility of coding structure presented in the next generation of video coding standard High Efficiency Video Coding standard HEVC allows the definition of various sizes of transform matrices which can vary from 4×4 to 32×32. This paper describes a unified hardware architecture for 4×4, 8×8, 16×16 and 32×32 inverse 2D core transform IDCT in HEVC standard. It used only one block 1D transform and a transpose buffer based on FIFO memory blocs instead of the traditional register array in order to further reduce the memory resources. The synthesis results under TSMC 180 nm CMOS technology show that the total gate count of the design is more than 30% improved compared to previous works. However, the operating frequency of the hardware design is about 130 MHz. This last can perform the decoding of 25 frames per second of Quad HD (3840×2160) resolution.

关键词： image processing Decision support systems Hafnium

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