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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

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A Lightweight Human Pose Estimation Algorithm Based on High Resolution Network 5

A Lightweight Human Pose Estimation Algorithm Based on High ...

引用

5th International conference on Natural Language processing, ICNLP 2023

作者： Ma, Sai Ge, Haibo He, Wenhao Huang, Chaofeng An, Yu Zhou, Ting Xi'an University of Posts and Telecommunication School of Electronic Engineering Xi'an China

ISBN: (纸本)9798350302219

Human pose estimation is an important research direction in the field of computer vision. At present, the mainstream human pose estimation algorithms have high complexity, large amount of calculation, and cannot be run on resource-constrained devices such as mobile terminals, which severely limits the popularization and application of this technology. Aiming at the problem of increased network model parameters and computational complexity, based on the High-Resolution Network (HRNet), a lightweight human pose estimation network incorporating Ghost module and attention mechanism is proposed. Replaced with Ghost convolution, and added the attention mechanism Concurrent Spatial and Channel Squeeze and Channel Excitation Net module on this basis to ensure the prediction accuracy of the network. Under the same image resolution and environment configuration, the experimental results on the COCO dataset show that the improved network model reduces the number of parameters by 98.3% compared to the high-resolution network model, and reduces the computational complexity by 67.6%. The experimental results show that the improved network model can effectively reduce the amount of network parameters and reduce the computational complexity while maintaining a certain prediction accuracy. © 2023 IEEE.

关键词： Computational complexity

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Unstructured Lane Identification Based on Hough Transform and Improved Region Growing 38

Unstructured Lane Identification Based on Hough Transform an...

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38th Chinese Control conference (CCC)

作者： Huang, Tianpeng Wang, Zhikai Dai, xi Huang, Deqing Su, Hu Southwest Jiaotong Univ Sch Elect Engn Chengdu Peoples R China

ISBN: (纸本)9789881563972

With the continuous development of intelligent driving technology, vision-based navigation technology is becoming increasingly significant. Lane detection is the key part of the navigation technology. At present, most of the researches focus on the identification of structured lane, such as highways. However, study on the detection of unstructured lane is relatively few, mainly because unstructured lanes have no obvious marks, which brings difficulties in identification. Therefore, unstructured lane detection still faces serious challenges now. In this paper, region of interest (ROI) of original RGB image is first selected. Next step is RGB image conversion to a grayscale. Then, Gaussian filter and mean filter are used to smooth the structured lane image and unstructured lane image, respectively. Finally, applying edge detection and Hough transform (HT) to extract the unstructured straight lane. Meanwhile, improved region growing and least square (LS) are used to extract unstructured curved lane. The experiment results on the roads of a campus show that the presented algorithms are effective, which can accurately extract the road area and road boundary.

关键词： Unstructured straight lane Unstructured curved lane Hough transform Improved region growing Least square

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Lossless layout compression for maskless lithography systems

Lossless layout compression for maskless lithography systems

引用

Emerging Lithographic Technologies IV conference

作者： Dai, V Zakhor, A Univ Calif Berkeley Dept Elect Engn & Comp Sci Video & Image Proc Lab Berkeley CA 94720 USA

ISBN: (纸本)0819436151

Future lithography systems must produce more dense chips with smaller feature sizes, while maintaining throughput comparable to today's optical lithography systems. This places stringent data-handling requirements on the design of any maskless lithography system. Today's optical lithography systems transfer one layer of data from the mask to the entire wafer in about sixty seconds. To achieve a similar throughput for a direct-write maskless lithography system with a pixel size of 25 nm, data rates of about 10 Tb/s are required. In this paper, we propose an architecture for delivering such a data rate to a parallel array of writers. In arriving at this architecture, we conclude that pixel domain compression schemes are essential for delivering these high data rates. To achieve the desired compression ratios, we explore a number of binary lossless compression algorithms, and apply them to a variety of layers of typical circuits such as memory and control. The algorithms explored include the Joint Bi-Level image processing Group (JBIG), Ziv-Lempel (LZ77) as implemented by ZIP, as well as our own extension of Ziv-Lempel to two-dimensions. For all the layouts we tested, at least one of the above schemes achieves a compression ratio of 20 or larger, demonstrating the feasibility of the proposed system architecture.

关键词： maskless lithography compression JBIG ZIP LZ77 layout pattern direct-write

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SAR processing UWB VHF data without a motion measurement system 25

SAR processing UWB VHF data without a motion measurement sys...

引用

conference on algorithms for Synthetic Aperture Radar imagery XXV

作者： Torgrimsson, Jan Dammert, Patrik Hellsten, Hans Ulander, Lars M. H. Ahlander, Anders Chalmers Univ Technol Gothenburg Sweden SAAB Surveillance Gothenburg Sweden

ISBN: (数字)9781510618060

ISBN: (纸本)9781510618060

SAR processing usually requires very accurate navigation data, i.e. to form a focused image. The track must be measured within fractions of the centre wavelength. For high frequencies (e.g. X-band) this condition is too strict. Even with a cutting-edge motion measurement system, autofocus is a necessity. For low frequencies (e.g. VHF-band) a differential GPS (DGPS) is often an adequate solution (alone). However, for this case, it is actually conceivable to rely on autofocus capability over the motion measurement system. This paper describes how to form a SAR image without support from navigation data. That is within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a base-2 fast factorized back-projection realization with six free geometry parameters (per sub-aperture pair). These are tuned step-by-step until a sharp image is obtained. This procedure can compensate for an erroneous geometry (from a focus perspective). The FGA algorithm has been applied successfully on an ultra-wideband (UWB) data set, acquired at VHF-band by the CARABAS 3 system. The track is measured accurately by means of a DGPS. We however adopt and modify a basic geometry model. A linear equidistant flight path at fixed altitude is assumed and adjusted at several resolution levels. With this approach, we emulate a stand-alone processing chain without support from navigation data. The resulting FGA image is compared to a reference image and verified to be focused. This indicates that it is feasible to form a VHF-band SAR image without a motion measurement system.

关键词： Autofocus Back-Projection FGA Synthetic Aperture Radar (SAR) UWB VHF

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An Accurate and Time-Efficient Subtractor by Cross Format Coding in Stochastic Computing

An Accurate and Time-Efficient Subtractor by Cross Format Co...

引用

IEEE Asia Pacific conference on Circuits and systems (APCCAS)

作者： Zhang, Zhihuai Zhang, Weiqian xiong, Shisheng Zhao, Yudi Fudan Univ Sch Informat Sci & Technol Micronano Syst Ctr Shanghai Peoples R China Beijing Informat Sci & Technol Univ Minist Informat Ind Key Lab Informat & Commun Syst Beijing Peoples R China

ISBN: (纸本)9781665450737

Different from binary computation, stochastic computation (SC), as a new paradigm, uses stochastic bit stream (SBS) to encode data. By simplifying computing elements, the circuit area can be greatly reduced. SBS can be generated by a stochastic number generator (SNG) with a variety of formats. In this work, we use unipolar (UP) and bipolar (BP) formats to optimize the traditional SC subtractor, which is named the UP-to-BP Subtractor (UBS). A new cross format coding (CFC) method is proposed for stochastic computing, which combines the UP and BP format, and is applied to Sobel edge detection in image processing algorithms. The fault tolerance and detection efficacy of the proposed CFC method and conventional binary computing are compared in this paper. By using the CFC method, the detected F-Score is improved by 0.15(23%). If the F-score remains unchanged, the processing speed can be about 10 times faster.

关键词： stochastic computing stochastic subtractor image processing edge detection

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Diffraction depth of focus in optical microscope

Diffraction depth of focus in optical microscope

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conference on Current Developments in Lens Design and Optical Engineering xi - and Advances in Thin Film Coatings VI

作者： Borovytsky, Volodymyr Fesenko, Andrey Nat Techn Univ Ukraine KPI Opt Eng Dept UA-03056 Kiev Ukraine

ISBN: (纸本)9780819482822

The paper presents the mathematical technique for calculation of the diffraction depth of focus of an optical system of a widefield microscope. The proposed technique applies the Rayleigh criterion based on evaluation of the wave aberration appeared due to defocus in a high aperture optical system. The maximal value of a linear approximation of the defocus wave aberration is used to define the depth of focus. It is proven that in optical systems with numerical aperture higher than 0.5 have the diffraction depth of focus 25 - 40% smaller than the widely known formula defines. This fact is important for implementation of autofocus and digital focus extension algorithms. The non-sophisticated formula for calculation of the depth of focus is proposed. The results of experimental measurements of the depth of focus are presented and discussed.

关键词： depth of focus wave aberration image quality Rayleigh criterion Marechal criterion

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Faster imaging simulation through complex systems: a coronagraphic example 11

Faster imaging simulation through complex systems: a coronag...

引用

conference on Optical Modeling and Performance Predictions xi

作者： Milani, Kian Douglas, Ewan S. Univ Arizona James C Wyant Coll Opt Sci Tucson AZ 85721 USA Univ Arizona Steward Observ MIT Tucson AZ 85721 USA

ISBN: (纸本)9781510637757

End-to-end simulation of the influence of the optical train on the observed scene is important across optics and is particularly important for predicting the science yield of astronomical telescopes. As a consequence of their goal of suppressing starlight, coronagraphic instruments for high-contrast imaging have particularly complex field-dependent point-spread-functions (PSFs). The Roman Coronagraph Instrument (CGI), Hybrid Lyot Coronagraph (HLC) is one example. The purpose of the HLC is to image exoplanets and exozodiacal dust in order to understand dynamics of solar systems. This paper details how images of exoplanets and exozodiacal dust are simulated using some of the most recent PSFs generated for the CGI HLC imaging mode. First, PSFs are generated using physical optics propagation techniques. Then, the angular offset of pixels in image scenes, such as exozodiacal dust models, are used to create a library of interpolated PSFs using interpolation and rotation techniques, such that the interpolated PSFs correspond to angular offsets of the pixels. This means interpolation needs only be done once and an image can then be simulated by multiplying the vector array of the model astrophysical scene by the matrix array of the interpolated PSF data. This substantially reduces the time required to generate image simulations by reducing the process to matrix multiplication, allowing for faster scene analysis. We will detail the steps required to generate coronagraphic scenes, quantify the speed-up of our matrix approach versus other implementations, and provide example code for users who wish to simulate their own scenes using publicly available HLC PSFs.

关键词： Point spread functions Coronagraphy Computer simulations Convolution Scene simulation image processing Wavefronts Exoplanets Imaging systems

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Design and Implementation of an AI-Driven Hybrid Framework for Risk Assessment 7

Design and Implementation of an AI-Driven Hybrid Framework f...

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7th International conference on Advanced algorithms and Control Engineering, ICAACE 2024

作者： Zhang, Haibo Yang, xi School Of Economics And Management Southwest University Of Science And Technology Dept. Of Economics And Management Mianyang China

ISBN: (纸本)9798350361445

This paper discusses key challenges of data processing in the field of artificial intelligence (AI), specifically in dealing with unstructured data and adapting to market changes. We propose a novel AI risk assessment framework by developing a multi-model hybrid scoring system that integrates machine learning and deep learning, focusing on random forests and long Short-Term memory (LSTM) networks. Experimental validation shows that our framework performs more effectively in accurate risk classification compared with existing SOTA methods, significantly enhancing the capabilities of AI systems in complex data environments. Our results provide a new perspective and technical approach for AI risk assessment, which plays a crucial role in the optimization and application of AI systems. © 2024 IEEE.

关键词： Long short-term memory

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Quantum-Dot Cellular Automata Design for Median Filtering and Mathematical Morphology Operations on Binary images

Quantum-Dot Cellular Automata Design for Median Filtering an...

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10th International conference on Cellular Automata for Research and Industry (ACRI)

作者： Panagiotopoulos, Fotios K. Mardiris, Vassilios A. Chatzis, Vassilios Department of Information Management Technological Institute of Kavala Greece

ISBN: (纸本)9783642333507

The continuing development of smaller electronic devices into the nanometer regime offers great possibilities of highly parallel computing systems, as it allows to reduce power consumption and device sizes and to increase operating speed. Quantum-dot Cellular Automata (QCA) has been proposed as an alternative for nanoelectronic devices and introduces a new opportunity for the design of highly parallel algorithms and architectures. Its benefits are the fast speed, very small size, high density and low energy consumption. These advantages can be very useful for various real time image processing applications. Complex image processing algorithms include in many cases the well-known binary median filter and mathematical morphology operations such as dilation and erosion. In this paper we propose and simulate two innovative QCA circuits which implement the dilation and the erosion.

关键词： Dot Cellular Automata circuit design circuit simulation nanoelectronics median filter mathematical morphology binary image

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Learning with Noisy Correspondence for Cross-modal Matching 35

Learning with Noisy Correspondence for Cross-modal Matching

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35th Annual conference on Neural Information processing systems (NeurIPS)

作者： Huang, Zhenyu Niu, Guocheng Liu, xiao Ding, Wenbiao xiao, xinyan Wu, Hua Peng, xi Sichuan Univ Coll Comp Sci Chengdu Peoples R China Baidu Inc Beijing Peoples R China TAL Educ Grp Beijing Peoples R China

ISBN: (纸本)9781713845393

Cross-modal matching, which aims to establish the correspondence between two different modalities, is fundamental to a variety of tasks such as cross-modal retrieval and vision-and-language understanding. Although a huge number of cross-modal matching methods have been proposed and achieved remarkable progress in recent years, almost all of these methods implicitly assume that the multimodal training data are correctly aligned. In practice, however, such an assumption is extremely expensive even impossible to satisfy. Based on this observation, we reveal and study a latent and challenging direction in cross-modal matching, named noisy correspondence, which could be regarded as a new paradigm of noisy labels. Different from the traditional noisy labels which mainly refer to the errors in category labels, our noisy correspondence refers to the mismatch paired samples. To solve this new problem, we propose a novel method for learning with noisy correspondence, named Noisy Correspondence Rectifier (NCR). In brief, NCR divides the data into clean and noisy partitions based on the memorization effect of neural networks and then rectifies the correspondence via an adaptive prediction model in a co-teaching manner. To verify the effectiveness of our method, we conduct experiments by using the image-text matching as a showcase. Extensive experiments on Flickr30K, MS-COCO, and Conceptual Captions verify the effectiveness of our method. The code could be accessed from ***. me.

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