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Intelligent technology and Embedded Systems (ICITES), International Conference on

作者： Dan Xie Haishan Tian Yuxin Sun Mingru Zhang Yawei Huang Chang Tang School of Physics and Electronics Hunan Normal University Changsha China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing China

The data rate of high-performance airborne sensors is much higher than the wireless data transfer rate in many detection applications, so the onboard data storage systems are usually used to store the sensor data. There is a problem in the onboard data storage that the frequency of address jumps among incontinuous areas is very high due to the high data updating frequency of the FAT (File Allocation Table) and FDT (File Directory Table), which would significantly reduce the data storage speed. This is because the most widely used NAND (Not And) flash has a long response time when storing the data in the incontinuous areas. In order to solve the problem, a called medium fusion storage method, which uses multiple mediums time sharing to store the data of file areas and data region, is proposed in this study. The performance of the proposed method is tested on an actual data storage system of the airborne sensor. The experimental results show that medium fusion storage method significantly reduces the data updating frequency of the FAT and FDT in the data storage, and the response time is negligible compared with the actual data writing time.

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Design and Implementation of High-Speed Serial Transmission for ADC Based on JESD204B

Design and Implementation of High-Speed Serial Transmission ...

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Intelligent technology and Embedded Systems (ICITES), International Conference on

作者： Yawei Huang Haishan Tian Mingru Zhang Yuxin Sun Dan Xie Chang Tang School of Physics and Electronics Hunan Normal University Changsha China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing China

Currently, as the resolution of sensors such as radar continues to improve, the signal bandwidth is rapidly increasing. There is a growing demand for higher sampling rates and data transmission rates in Analog-to-Digital Converters (ADCs). However, the parallel transmission commonly used in ADCs faces issues such as high crosstalk and difficulties in transmission synchronization. In response to this problem, this paper proposes a method for the design and implementation of a high-speed serial data transmission interface based on JESD204B. Specifically, it utilizes Xilinx's ZYNQ-7 series FPGA and ADC as the core components and presents clock synchronization design, ADC circuit design, and FPGA 204B IP design methods. Experimental testing was conducted using selected link parameters (LMFS=4222) as an example. The experimental results demonstrate that correct JESD204B interface data transmission for four channels was achieved at a data rate of 10 Gbps, thus validating the feasibility of the proposed high-speed transmission link design based on JESD204B in this paper.

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Thermal camera based on frequency upconversion and its noise-equivalent temperature difference characterization

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Advanced Photonics Nexus 2023年第4期2卷 44-49页

作者： Zheng Ge Zhi-Yuan Zhou Jing-Xin Cheng Li Chen Yin-Hai Li Yan Li Su-Jian Niu Bao-Sen Shi University of Science and Technology of China CAS Key Laboratory of Quantum InformationHefeiChina University of Science and Technology of China CAS Center for Excellence in Quantum Information and Quantum PhysicsHefeiChina Science and Technology on Electro-Optical Information Security Control Laboratory TianjinChina

We present a scheme for estimating the noise-equivalent temperature difference(NETD)of frequency upconversion detectors(UCDs)that detect mid-infrared(MIR)*** particular,we investigate the frequency upconversion of a periodically poled crystal based on lithium niobate,where an MIR conversion bandwidth of 220 nm can be achieved in a single-poled period by a special ***,for an MIR radiating target at a temperature of 95℃,the NETD of the device was estimated to be 56 mK with an exposure time of 1 ***,a direct measurement of the NETD was performed utilizing conventional methods,which resulted in 48 *** also compared the NETD of our UCD with commercially available direct MIR *** show that the limiting factor for further NETD reduction of our device is not primarily from the upconversion process and camera noise but from the limitations of the heat source and laser *** detectors have good temperature measurement performance and can be used for a variety of applications involving temperature object identification and material structure detection.

关键词： mid-infrared detection frequency upconversion noise equivalent temperature difference

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Multi-view infrared small target recognition based on YOLOv5

Multi-view infrared small target recognition based on YOLOv5

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Chinese Automation Congress (CAC)

作者： Hua Gong Shasha Liu Song Guan Kuaikuai Yu Fang Liu College of Science Shengyang Ligong University Shenyang China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing China

In order to improve the recognition accuracy of small infrared targets in complex environment, a SyluInfrared dataset is built by taking multi-view infrared images with the Frock TiX600 infrared thermal imager. Seven image enhancement algorithms including image brightening, contrast adjustment, image blurring, image flipping and image scaling are designed to improve the image quality of small infrared targets. The YOLOv5 deep learning model is used to identify small infrared targets with multiple views to improve the recognition accuracy of small infrared targets. The experimental results show that the accuracy of multi-view infrared small target recognition model for YOLOv5 deep network is 97.7%, which is 6.6% higher than that of single-view infrared small target recognition model based on YOLOv5. The multi-view target recognition strategy significantly improves the infrared small target recognition performance.

关键词： Image quality Deep learning Image recognition Automation Target recognition Object detection Data models

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Infrared Target Detection Based on the Fusion of Mask R-CNN and Image Enhancement Network

Infrared Target Detection Based on the Fusion of Mask R-CNN ...

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Chinese Automation Congress (CAC)

作者： Fang Liu Song Guan Kuaikuai Yu Hua Gong College of Science Shengyang Ligong University Shenyang China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing China

In this paper, we focus on the problem of the infrared image detection. Aiming at the problem of the low contrast of the infrared images, an adaptive gamma transformation algorithm (AGT) is established to intelligently improve the contrast of the infrared images. Aiming at the problem of the weak edge information of the infrared images, an improved Sobel operator edge enhancement algorithm (ISOEE) is designed to enrich the edge features of the infrared images. In order to solve the problem that the traditional infrared image detection algorithm relies on expert experience, the fusion infrared images detection model AIE-Mask R-CNN based on Mask R-CNN, AGT algorithm and ISOEE algorithm is proposed. This fusion model can realize accurate and intelligent detection for the infrared images. The experimental results show that the fusion model AIE-Mask R-CNN improves the detection accuracy of the infrared images.

关键词： Adaptation models Automation Image edge detection Object detection Detection algorithms Image enhancement

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Accelerating High-resolution Image Stitching for the Dual Camera System based on GPU

Accelerating High-resolution Image Stitching for the Dual Ca...

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Chinese Automation Congress (CAC)

作者： Jingsi Wang Dong Liu Ran Zheng Yongcai Hu Wu Gao Chen Zhao School of Computer Science Northwestern Polytechnical University Xi’an China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin China

Image stitching plays an important role in the field of computer vision and image processing. Although some sophisticated stitching methods have been proposed, they are usually time-consuming. Because many application scenarios, such as video surveillance, need quick image stitching to provide a wide field of view, accelerating the image stitching is critical. In recent years, the neural network is used to stitching images, but only relatively small size images can be processed; meanwhile, time-consuming image stitching is also unavoidable. In this paper, to quickly stitch 1920×1080 images generated by the dual camera system, an image stitching algorithm is proposed. We divided the algorithm depending on its timeliness on different steps, and its time-consuming steps are parallelized on Graphics Processing Unit (GPU) platforms to be accelerated. We tested different hierarchies for organization of threads and access of memory on compute unified device architecture (CUDA) programming, and the final experiment results showed that our algorithm could reach a speedup ratio up to 119x on the Desktop with 3080ti.

关键词： Image registration Neural networks Merging Graphics processing units Organizations Programming Cameras

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Thermal camera based on frequency upconversion and its NETD characterization

arXiv

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arXiv 2023年

作者： Ge, Zheng Zhou, Zhi-Yuan Ceng, Jing-Xin Chen, Li Li, Yin-Hai Li, Yan Niu, Su-Jian Shi, Bao-Sen CAS Key Laboratory of Quantum Information University of Science and Technology of China Anhui Hefei230026 China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei230026 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300308 China

We present a scheme for estimating the noise-equivalent temperature difference (NETD) of frequency upconversion detectors (UCDs) that detect mid-infrared (MIR) light. In particular, this letter investigates the frequency upconversion of a periodically polarized crystal based on lithium niobate, where a mid-infrared conversion bandwidth of 220 nm can be achieved in a single poled period by a special design. Experimentally for a temperature target with a central wavelength of 7.89 μm in mid-infrared radiation, we estimated the NETD of the device to be 56 mK. Meanwhile, a direct measurement of the NETD was performed utilizing conventional methods, which resulted in 48 mK. We also compared the NETD of our UCD with commercially available direct mid-infrared detectors. Here, we showed that the limiting factor for further NETD reduction of our device is not primarily from the upconversion process and camera noise, but from the limitations of the heat source performance. Our detectors have good temperature measurement performance and can be used for a variety of applications involving temperature object identification and material structure detection. Copyright © 2023, The Authors. All rights reserved.

关键词： Temperature measurement

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Integrating Parafac and Pso Fitting Model: A New View into Fluorescence Spectroscopic Analysis for Adulterant Quantification of Lubricant Oil

SSRN

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SSRN 2024年

作者： Zhang, Lujun Cai, Nuo Wang, Yan Fan, Xinmin Gao, Juanjuan Gao, Jin Li, Sensen Lan, Christopher Q. Xiaodong, Huang Wang, Chunyan Department of Physics and Electronic Information Weifang University Weifang261061 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300308 China Department of Chemical & Biological Engineering University of Ottawa OttawaONK1N 6N5 Canada

The adulteration of high-quality engine lubricants with inferior, dubious alternatives or reclaimed oils presents a significant challenge, necessitating the development of precise and rapid detection methodologies. This study introduces a novel analytical approach of excitation-emission matrix fluorescence (EEMF) spectroscopy paired with parallel factor analysis (PARAFAC) for the quantification of adulterants within adulterated lubricant samples. A fitting model is introduced to establish a correlation between the PARAFAC component scores of pure adulterants and those of adulterated samples. Furthermore, particle swarm optimization (PSO) is employed to refine the fitting parameters within this model, enabling the determination of individual adulterant' relative quantities in adulterated samples. This methodology not only broadens the application of EEMF combined with PARAFAC for adulteration quantification but also shows potential as a universal quantitative analysis tool for diverse complex fluorophobic mixtures. © 2024, The Authors. All rights reserved.

关键词： Fluorescence

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Design Compact YOLO based Network for Small Target Detection on Infrared Image

Design Compact YOLO based Network for Small Target Detection...

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Chinese Automation Congress (CAC)

作者： Shuang Liu Zhicheng Liu Yuhai Li Wancheng Liu Chenyang Ge Longjun Liu Institute of Artificial Intelligence and Robotics (IAIR) Xi’an Jiaotong University Xi’an China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin China

most YOLO object detection neural networks prefer to focus on traditional RGB image, but previous studies rarely consider special YOLO network with compact architecture for infrared image. In this paper, we analyze original YOLO network architecture, and we propose a compact YOLO based network by using different blocks from previous work for small target detection on infrared image. We use small target detection layer, GhostConv convolution, Focus structure, Focal EIOU Loss and soft NMS modules to improve original YOLO network structure, which improves the accuracy and speed of target detection for infrared image. The experimental results show that the accuracy of target detection of original model can be effectively improved by adding the small target detection layer, the Focus structure and the BI-FPN structure. By replacing the GhostConv convolution, the calculation speed is significantly improved. At last, after the model is quantized and deployed with NCNN framework, the object detection speed can reached to 35ms per infrared image.

关键词： Automation Convolution Neural networks Object detection Network architecture

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Design an Efficient DNN Inference Framework with PS-PL Synergies in FPGA for Edge Computing

Design an Efficient DNN Inference Framework with PS-PL Syner...

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Chinese Automation Congress (CAC)

作者： Wancheng Liu Yuhai Li Yining Yang Jinyu Zhu Longjun Liu Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin China Institute of Artificial Intelligence and Robotics (IAIR) Xi’an Jiaotong University Xi’an China

in recent years, Deep Neural Network (DNN) based methods have achieved great success for changing inflexible machine to intelligent and live system. Internet of Things (IoT) applications equipped with DNN in domains such as self-driving, speech processing and video surveillance particular challenges. Since DNNs are memory-/computing- intensive applications, FPGAs are customized to accelerate DNN on edge system due to their low latency and high energy efficiency. However, embedded CPU is usually essential for IoT system and single accelerator of FPGA is hard to gain maximized performance of the whole IoT system. Therefore, we design an efficient DNN inference framework with programming system (PS, e.g., ARM CPU) and programming logic (PL, e.g. FPGA) synergies for intelligent IoT system. Compared with the common IoT system only separately leverages FPGA for DNN accelerating and ARM for other tasks, our framework can make ARM and FPGA jointly accelerate DNN inference from the beginning. Our PS-PL co-design approach can take full advantage of the merits of ARM (control operations) and FPGA (parallel computing operations) for various DNN model accelerating. We implemented our co-design framework on Zynq SoCs. The experimental results show that our framework can achieve maximal 205.9 GOPs/s DNN inference accelerating under 6.2W while it would not affect other CPU tasks running on IoT system.

关键词： Program processors Computational modeling Neural networks Programming Parallel processing Video surveillance Internet of Things

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