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2019 IEEE International Conference on signal, information and Data processing, ICSIDP 2019

作者： Li, Huixing Gao, Zixin Li, Bingyi Xie, Yi Zhuang Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Beijing Institute of Radio Measurement Beijing China

ISBN: (纸本)9781728123455

Aiming at the problem of insufficient memory in the real-time processing of SAR imaging on embedded TX2, this paper studies a design optimization scheme of fixed-point imaging algorithm on TX2. In order to ensure the accuracy, this paper only performs fixed-point processing on the FFT. According to the characteristics of the algorithm, the memory multiplexing method is adopted to effectively reduce the occupation of the work area buffer. A large number of registers are used to improve computing performance. The results show that the fixed-point FFT processing scheme can achieve a hundred times faster than the Intel Xeon CPU, and the memory footprint is less. © 2019 IEEE.

关键词： Fast Fourier transforms

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An improved inverse synthetic aperture radar range alignment method based on maximum contrast

An improved inverse synthetic aperture radar range alignment...

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IET International radar Conference 2018, IRC 2018

作者： Li, Yong Zhang, Tianyi Ding, Zegang Gao, Wenbin Chen, Jing Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing100081 China

Inverse synthetic aperture radar (ISAR) is an important tool for non-cooperative ship imaging, and one key step of ISAR imaging is range alignment. To achieve the range alignment with high precision, efficiency and robustness, an improved ISAR range alignment method based on maximum contrast is proposed in this paper, which takes the maximum contrast of average range profile as the optimisation criterion to perform the range alignment. Compared with the minimum entropy method, this method is with lower computation complexity and faster convergence rate. Thus the method proposed in this article is more effective and more robust. Computer simulation and real data experiment validate the effectiveness and robustness of the proposed method. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Inverse synthetic aperture radar

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Efficiency balanced matrix transpose method for sliding spotlight SAR imaging processing

Efficiency balanced matrix transpose method for sliding spot...

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IET International radar Conference 2018, IRC 2018

作者： Sun, Tianyuan Xie, Yizhuang Li, Bingyi Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing100081 China

Matrix transposition is a very critical operation in synthetic aperture radar (SAR) imaging systems. This study presents an improved corner turning memory solution for real-time SAR imaging processing. Based on the sub-matrix three-dimensional mapping method, the efficiency of matrix transposing is greatly increased. However, in sliding spotlight mode, a novel SAR imaging mode, the amount of raw data is increased too large to directly use the above method. In this study, a joint address mapping strategy for two pieces of double data rate 3 synchronous dynamic random-access memory is used to meet the needs of the amount of data and make up for the lack of original method. The experimental results show that this method can get an improved and balanced two-dimensional access efficiency for sliding spotlight mode SAR imaging processing. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Mapping

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Generation scheme of chirp scaling phase functions based on floating-point CORDIC processor

Generation scheme of chirp scaling phase functions based on ...

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IET International radar Conference 2018, IRC 2018

作者： Fang, Linlin Xie, Yizhuang Li, Bingyi Chen, He Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing100081 China

This study presents a chirp scaling (CS) phase function generation scheme based on CORDIC algorithm, it adopts single precision floating-point CORDIC processor to implement a variety of non-linear operations which are involved in CS synthetic aperture radar (SAR) imaging algorithm. We extend the range of convergence of CORDIC algorithm and reduce the data width in rotation unit module by adopting a hardware resource reduction scheme. We also adopt a unified CORDIC processor to achieve square root, multiplication, and division operation, which can substitute multiple single-function processors and simplify the complicate arithmetic in CS algorithm. As a proof of concept, we verify the performance of the proposed design scheme on Xilinx XC7VX690T FPGA platform, it is also applied to 16384 × 16384 points target SAR imaging system, the FPGA resource occupancy of the CS phase function generation module demonstrates that the usage of CORDIC processor can effectively save the consumption of hardware resources, and the maximum operating frequency is acceptable. The accuracy of phase functions can satisfy the engineering requirements. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Field programmable gate arrays (FPGA)

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AutoHR: A strong end-To-end baseline for remote heart rate measurement with neural searching

arXiv

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arXiv 2020年

作者： Yu, Zitong Li, Xiaobai Niu, Xuesong Shi, Jingang Zhao, Guoying Center for Machine Vision and Signal Analysis University of Oulu Oulu90014 Finland Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications (e.g., remote healthcare). Existing end-To-end rPPG and heart rate (HR) measurement methods from facial videos are vulnerable to the less-constrained scenarios (e.g., with head movement and bad illumination). In this letter, we explore the reason why existing end-To-end networks perform poorly in challenging conditions and establish a strong end-Toend baseline (AutoHR) for remote HR measurement with neural architecture search (NAS). The proposed method includes three parts: 1) a powerful searched backbone with novel Temporal Difference Convolution (TDC), intending to capture intrinsic rPPGaware clues between frames;2) a hybrid loss function considering constraints from both time and frequency domains;and 3) spatiotemporal data augmentation strategies for better representation learning. Comprehensive experiments are performed on three benchmark datasets to show our superior performance on both intra-and cross-dataset testing. Copyright © 2020, The Authors. All rights reserved.

关键词： Convolution

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基于强弱对流耦合提高蒸发器性能以及梯级应用探索（英文）

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Science Bulletin 2025年第8期 1264-1274页

作者：李政通张嘉汉张静燕鹏杨涛杨超林鹏孟陶陶安盟周英棠徐兴涛 The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentState Key Laboratory of Hydrology-Water Resources and Hydraulic EngineeringHohai University Electronic-Photonic Smart Sensing Device R&D Team Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal ProcessingSchool of Electronic Information EngineeringInner Mongolia University Ningbo Key Laboratory of Green Petrochemical Carbon Emission Reduction Technology and Equipment Zhejiang Institute of Tianjin University Department of Mechanical Engineering The University of Tokyo Marine Science and Technology College Zhejiang Ocean University College of Material Science and Engineering Nanjing Forestry University

Modulating the macro/nanoarchitecture of evaporators to effectively harness diverse renewable energy sources is of paramount importance for optimizing the performance of solar-driven interfacial *** by the geometric structure of a windmill,we designed an innovative solar evaporator that expertly harnesses both strong and weak *** the purification of heavy metal wastewater,the maximum evaporation rate can reach 4.95 kg m-2h-1under one sun irradiation by introducing an ultralow wind flow (0.1 m s-1),yielding an evaporation rate that is twice that of traditional ***,the gradual deposition of inorganic salt sediments on the evaporator surface is clearly *** address this issue,we present several innovative proof-of-concept cascade treatments that significantly extend the evaporator’s operational *** innovative design and exceptional performance of this solar evaporator open avenues for advancements in sustainable water treatment,energy generation,and environmental remediation.

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Semantic knowledge transfer for semi-supervised medical image segmentation

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Engineering Applications of Artificial Intelligence 2025年 158卷

作者： Shiwei Zhou Haifeng Zhao Leilei Ma Dengdi Sun Key Laboratory of Intelligent Computing & Signal Processing (ICSP) Ministry of Education Anhui University Hefei 230601 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Hefei 230601 China School of Computer Science and Technology Anhui University Hefei 230601 China School of Artificial Intelligence Anhui University Hefei 230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei 230026 China

In semi-supervised medical image segmentation, due to possible differences in information content and distribution between labeled and unlabeled data, dealing with the two separately usually prevents knowledge transfer from labeled to unlabeled data. This prevents the model from effectively sharing learned information between the two types of data. To alleviate this problem, we train labeled and unlabeled data as a whole. Semantic mixing of labeled and unlabeled data is achieved by selecting and exchanging some of the region images of both through a mask to generate complementary input views. In addition, due to the limited labeled data, the unlabeled data has a weak ability to distinguish categories in the feature space. Traditional methods rely on pixel positions to generate positive and negative samples for contrastive learning to solve this problem, but relying on pixel position sampling can easily lead to semantic inconsistency, which affects the effect of feature learning; therefore, to address this problem, we propose an innovative labeled data-guided inter-class contrastive learning strategy, which extracts the category features from labeled and unlabeled data and exploits the accurate category information in the labeled data to guide contrastive learning, while introducing a similarity-based ranking weighting mechanism. Combining the two designs, we propose a new semantic knowledge transfer framework for semi-supervised medical image segmentation. Experiments demonstrate a significant improvement in our model compared to State of the Art (SOTA) on the Automatic Cardiac Diagnosis Challenge (ACDC) dataset and the Left Atrium (LA) dataset.

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Parallel processing of sliding spotlight mode SAR imaging based on GPU

Parallel processing of sliding spotlight mode SAR imaging ba...

引用

IET International radar Conference 2018, IRC 2018

作者： Gao, Zixin Wei, Chunpeng Yang, Chen Xie, Yizhuang Chen, He Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

Sliding spotlight synthetic aperture radar (SAR) is a hot imaging mode in space-borne SAR. It can acquire high-resolution and large azimuth scene size simultaneously. The main challenges for sliding spotlight SAR processing in real time are the huge volume of raw data and complex imaging algorithm. The rapid development of the graphics processing units (GPUs) provides a new computing platform for high-performance SAR processing. This work presents a parallel processing of sliding spotlight SAR imaging algorithm on GPU via compute unified device architecture and tests the speedup of each module of the algorithm on the K20c GPU platform from the aspect of a small granularity and a large granularity of point target images. Compared with traditional CPU-based SAR imaging technology, the proposed GPU-based sliding spotlight SAR imaging obtains a speedup of 186.80 when processing data with a granularity of 16,384 × 8192 and gets a speedup of 49.72 when processing data with a granularity of 65,536 × 32,768, thereby greatly improving the real-time imaging processing. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Graphics processing unit

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FPGA-based fault injection design for 16K-point FFT processor

FPGA-based fault injection design for 16K-point FFT processo...

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IET International radar Conference 2018, IRC 2018

作者： Mao, Chuang-An Xie, Yu Wei, Xin Xie, Yi-Zhuang Chen, He Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

There are a number of satellites working in the harsh space environment. The charged particles in space may strike the electron devices causing the undesired influences, such as soft errors in memory devices or permanent damage in hardware circuits. Aiming at reliability evaluation of very-large-scale integration circuits implemented in SRAM-based field programmable gate arrays, a fault injection platform is constructed based on the soft error mitigation controller in this study. The authors adopt a 16K-point fast Fourier transformation processor as the design under test (DUT) and inject errors into different positions. The effectiveness of this platform is varied by comparing the results of DUT with Golden data. Compared with the traditional reliability testing techniques, the fault injection method proposed in this study has the advantages of low cost, short test period and low resource consumption. Hence, the proposed fault injection design is suitable for circuits consuming huge resources and large number of repeating tests. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Static random access storage

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Multi-scale object detection by bottom-up feature pyramid network

Multi-scale object detection by bottom-up feature pyramid ne...

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IET International radar Conference 2018, IRC 2018

作者： Boya, Zhao Baojun, Zhao Linbo, Tang Chen, Wu Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China

The deep neural networks has been developed fast and shown great successes in many significant fields, such as smart surveillance, self-driving and face recognition. The detection of the object with multi-scale and multi-aspect-ratio is still the key problem. In this study, the authors propose a bottom-up feature pyramid network, coordinating with multi-scale feature representation and multi-aspect-ratio anchor generation. Firstly, the multi-scale feature representation is formed by a set of fully convolutional layers which is catenated after the backbone network. Secondly, in order to link the multi-scale feature, the deconvolutional layer is involving after each multi-scale feature map. Thirdly, to tackle the problem of adopting object with different aspect ratios, the anchors on each multi-scale feature map are generated by six shapes. The proposed method is evaluated on PASCAL visual object detection dataset and reach the accuracy of 80.5%. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Aspect ratio

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