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

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AIRCRAFT GROUND MONITORING WITH HIGH PERFORMANCE COMPUTING MULTICORE ENABLED VIDEO TRACKING 33

AIRCRAFT GROUND MONITORING WITH HIGH PERFORMANCE COMPUTING M...

引用

IEEE/AIAA 33rd Digital Avionics systems conference (DASC)

作者： Jia, Bin Ling, Haibin Blasch, Erik Sheaff, Carolyn Chen, Genshe Wang, Zhonghai Intelligent Fus Technol Inc Germantown MD 20876 USA Temple Univ Philadelphia PA 19122 USA Air Force Res Lab Rome NY USA

ISBN: (纸本)9781479950027

Safety of aircraft requires resiliency from on-board and off-board threats that could come from natural or man-made disturbances. Maintaining situation awareness requires monitoring and coordination of threats from the air and the ground. Threat detection of people, vehicles, and person-vehicle interactions of possible harm to an aircraft operations is a difficult problem due to the complexity of the coverage area, varying sensor capabilities (e.g., resolutions), and cultural factors of disruption. Methods and techniques can be incorporated to aid analysts (e.g., airport traffic controllers) to track and identify entities using modern large scale visual sensors such as the Wide Area Motion imagery (WAMI) systems. Such systems typically produce an overwhelmingly large amount of information. The lack of computationally efficient algorithms has become a bottleneck for utilizing WAMI data in surveillance. To facilitate the application of such surveillance system development for safe operations, in this paper, three different strategies are implemented based on the on-board multicore technology to speed up video tracking algorithms. A complete tool chain to implement the video tracking, such as registration, detection, and multiple target association, is presented. Experimental results are illustrated. We demonstrate aircraft ground monitoring using the Columbus Large image Format (CLIF) dataset to show the performance improvement by using the proposed high performance computing enabled video tracking algorithm to facilitate safe air travel.

关键词： Algorithm design and analysis Context Feature extraction Multicore processing Surveillance Target tracking Vehicles

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ENHANCED BIT-RATE PERFORMANCE FOR VISIBLE LIGHT COMMUNICATION systems BETWEEN LED AND MOBILE CAMERA 10

ENHANCED BIT-RATE PERFORMANCE FOR VISIBLE LIGHT COMMUNICATIO...

引用

10th IEEE International conference on Communications and Electronics (IEEE ICCE)

作者： Nam Hoang Nguyen Quan Dinh Nguyen Hanoi Univ Sci & Technol HUST Sch Elect & Elect Engn Hanoi Vietnam Hanoi Univ Sci & Technol HUST Sch Elect & Elect Engn Dept Automat Hanoi Vietnam

ISBN: (纸本)9798350379808;9798350379792

Multiple Pulse Position Modulation (MPPM) has become an important method in optical communication, especially between LEDs and mobile cameras. This paper proposes an MPPM modulation and demodulation method for Visible Light Communication (VLC) systems using LED bulbs and the camera for the transceiver that addresses data transmission performance barriers when increasing the distance between receiver and transmitter, as well as helps minimize comparison error rates compared with other modulation techniques. The PPM and MPPM modulation methods are both highly rated for their power and bandwidth efficiency. Using binary codes and image data processing algorithms at the receiver, along with optimized mapping, aids in minimizing character errors and enhancing communication performance. Additionally, integrating MPPM into the VLC system solves the problem of brightness control in real-world scenarios. The MPPM-based brightness control system is capable of dynamically adjusting brightness, providing higher communication performance and stability for the VLC system.

关键词： Multiple Pulse Position Modulation (MPPM) Visible Light Communication (VLC) Optical Camera Communication (OCC) image processing CMOS sensor

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Single image Super-Resolution Based on Enhanced Residual Neural Network 14

Single Image Super-Resolution Based on Enhanced Residual Neu...

引用

14th International conference on Signal processing systems, ICSPS 2022

作者： Zhao, Jie Chen, Zhenxue Liu, Chengyun Yang, Yue Ye, Mengting Zhang, Yujiao The School of Control Science and Engineering Shandong University Jinan China Information Tech Co Ltd China Mobile Comm Corp Hangzhou China Shenzhen Research Institute Shandong University Shenzhen China

ISBN: (纸本)9798350336313

Vision is an important way for humans to perceive the world around them. It is an urgent need to improve image quality by using image super resolution. Residual network plays an important role in image super resolution because of its powerful feature extraction ability. Only stacking residual network is not enough to extract a large amount of effective information, and at the same time, more training memory is needed. Therefore, this paper designs a single feature extraction module with better performance to enhance the feature extraction ability of the network. In this paper, the Residual Network is mainly improved, and a Single image Super-Resolution Based on Enhanced Residual Neural Network (ERNN) is proposed based on improved residual module. Compared with other classical lightweight algorithms, the lightweight network with the new residual module as the basic unit has higher reconstruction ability, and can achieve better image super-resolution reconstruction with a small number of parameters. Moreover, a large number of experiments have verified that the proposed ERNN can achieve the trade-off between the number of parameters and performance. © 2022 IEEE.

关键词： Feature extraction

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Hierarchy-Agnostic Unsupervised Segmentation: Parsing Semantic image Structure 38

Hierarchy-Agnostic Unsupervised Segmentation: Parsing Semant...

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38th conference on Neural Information processing systems, NeurIPS 2024

作者： Rossetti, Simone Pirri, Fiora DIAG Sapienza University of Rome Italy DeepPlants Italy

Unsupervised semantic segmentation aims to discover groupings within images, capturing objects' view-invariance without external supervision. Moreover, this task is inherently ambiguous due to the varying levels of semantic granularity. Existing methods often bypass this ambiguity using dataset-specific priors. In our research, we address this ambiguity head-on and provide a universal tool for pixel-level semantic parsing of images guided by the latent representations encoded in self-supervised models. We introduce a novel algebraic approach that recursively decomposes an image into nested subgraphs, dynamically estimating their count and ensuring clear separation. The innovative approach identifies scene-specific primitives and constructs a hierarchy-agnostic tree of semantic regions from the image pixels. The model captures fine and coarse semantic details, producing a nuanced and unbiased segmentation. We present a new metric for estimating the quality of the semantic segmentation of discovered elements on different levels of the hierarchy. The metric validates the intrinsic nature of the compositional relations among parts, objects, and scenes in a hierarchy-agnostic domain. Our results prove the power of this methodology, uncovering semantic regions without prior definitions and scaling effectively across various datasets. This robust framework for unsupervised image segmentation proves more accurate semantic hierarchical relationships between scene elements than traditional algorithms. The experiments underscore its potential for broad applicability in image analysis tasks, showcasing its ability to deliver a detailed and unbiased segmentation that surpasses existing unsupervised methods. © 2024 Neural information processing systems foundation. All rights reserved.

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image Compression and Reconstruction Based on Quantum Network

Image Compression and Reconstruction Based on Quantum Networ...

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1st International conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Ji, Xun Liu, Qin Huang, Shan Chen, Andi Wu, Shengjun Nanjing Univ Sch Phys Natl Lab Solid State Microstruct Nanjing 210093 Peoples R China Nanjing Univ Collaborat Innovat Ctr Adv Microstruct Nanjing 210093 Peoples R China Nanjing Univ Inst Brain Sci Nanjing 210023 Peoples R China Nanjing Univ Kuang Yarning Honors Sch Nanjing 210023 Peoples R China Univ Sci & Technol China Hefei Natl Lab Hefei 230088 Peoples R China

ISBN: (纸本)9798350364613;9798350364606

Quantum network is an emerging type of network structure that leverages the principles of quantum mechanics to transmit and process information. Compared with classical data reconstruction algorithms, quantum networks make image reconstruction more efficient and accurate. They can also process more complex image information using fewer bits and faster parallel computing capabilities. Therefore, this paper will discuss image reconstruction methods based on our quantum network and explore their potential applications in image processing. We will introduce the basic structure of the quantum network, the process of image compression and reconstruction, and the specific parameter training method. Through this study, we can achieve a classical image reconstruction accuracy of 97.57%. Our quantum network design will introduce novel ideas and methods for image reconstruction in the future.

关键词： image compression and reconstruction quantum network parameter training

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Detection of Bruise Damage of Pear Using Hyperspectral imagery

Detection of Bruise Damage of Pear Using Hyperspectral Image...

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12th International conference on Control, Automation and systems (ICCAS)

作者： Dang, Hong-Quan Kim, Intaek Cho, Byoung-Kwan Kim, Moon S. Myongji Univ Dept Informat & Commun Engn Yongin South Korea Chungnam Natl Univ Biosystems Machinery Engn Dept Daejeon South Korea

ISBN: (纸本)9788993215045

Over the past decade, hyperspectral imaging has been an exciting technology used in many practical fields. In agriculture, hyperspectral imaging is implemented in controlling fruit quality and analyzing specific crops in different estimated climate. Bruise damage is one of the crucial factors that influence significantly quality of fruits. This paper focuses on combining hyperspectral imaging with some supervised classification including k-nearest neighbor (k-NN) and support vector machine (SVM) algorithm to detect bruise areas on pears. Data acquisition of hyperspectral NIR reflectance images of pears was performed for choosing the feature of classification algorithms. Experiment results show the effectiveness of both methods in separating bruise from normal areas in shortest time. These results are good enough to detect the early bruise damage which is not easily recognized by conventional classification methods using human eye.

关键词： Hyperspectral imaging bruise pears image processing and supervised classification

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Media processing applications on the imagine stream processor

Media processing applications on the imagine stream processo...

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20th IEEE International conference on Computer Design

作者： Owens, JD Rixner, S Kapasi, UJ Mattson, P Towles, B Serebrin, B Dally, WJ Stanford Univ Comp Syst Lab Stanford CA 94305 USA

ISBN: (纸本)0769517005;0769517013

Media applications, such as image processing, signal processing, video, and graphics, require high computation rates and data bandwidths. The stream programming model is a natural and powerful way to describe these applications. Expressing media applications in this model allows hardware and software systems to take advantage of their concurrency and locality in order to meet their high computational demands. The Imagine stream programming system, a set of software tools and algorithms, is used to program media applications in the stream programming model. We achieve real-time performance on a variety of media processing applications with high computation rates (4-15 billion achieved operations per second) and high efficiency (84-95% occupancy on the arithmetic clusters).

关键词： Computer aided software engineering

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image SEGMENTATION APPLIED TO CT EXAMINATION OF LYMPHANGIOLEIOMYOMATOSIS (LAM)

IMAGE SEGMENTATION APPLIED TO CT EXAMINATION OF LYMPHANGIOLE...

引用

conference on image processing

作者： EVERHART, J CANNON, M NEWELL, J LYNCH, D LOS ALAMOS NATL LAB LOS ALAMOSNM 87545

ISBN: (纸本)081941462X

The purpose of this study is to use modern image segmentation techniques to quantitate cyst area and number within a complete CT examination of the lungs. Lymphangioleiomyomatosis (LAM) was chosen because this disease produces many well defined thin- walled cysts of varying sizes throughout the lungs that provide a good test for 2D image segmentation techniques, which are used to separate LAM cysts from the normal lung tissue. Quantitative measures of the lung, such as cyst area versus frequency, are then automatically extracted. Three women with LAM were examined using CT slices obtained at 20 mm intervals, with 1 to 1.5 mm collimation, and a pixel size of 0.4 - 0.5 mm. Our segmentation algorithm operates in several stages. First, masks for each lung are automatically generated, thus allowing only lung pixels to be considered for the cyst segmentation. Next, we threshold the data under the masks at a level of -900 Hounsfield units. The threshold segments LAM cysts from normal lung tissue and other structures, such as pulmonary veins and arteries. In order to determine the size of individual cysts, we grow all regions having brightness values lower than the threshold within the masked regions. These regions, which correspond to cysts, are then sorted by size, and a cyst histogram for each patient is computed.

关键词： Lung image segmentation Computed tomography Tissues image processing image processing algorithms and systems Blood Collimation Lymphatic system Veins

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Real-time infrared target tracking system design and research based on DSP

Real-time infrared target tracking system design and researc...

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conference on Neural Network and Distributed processing

作者： Xu, XH Tao, R Wang, Y Beijing Inst Technol Informat Syst Lab Dept Elect Engn Beijing 100081 Peoples R China

ISBN: (纸本)0819442836

Based on the Digital Signal Processor (ADSP21060), a principal and subordinate structure parallel real time infrared target tracking system is established. The system is composed of image acquisition sub system, image processing subsystem, manual control subsystem and target indicates subsystem. A new fast two-dimensional (2-D) entropy algorithm and motion target detection algorithm is implemented in second DSP to detect infrared target. The mass centered tracking algorithm and correlative-tracking algorithm are used to tracking targets. A Kalman filter algorithm is used to predicting approach. And using ADSP21060 to achieve the Kalman filtering algorithm and satisfies the real-time need. In this tracking system the tracking state of infrared target is considered, detecting algorithm or tracking algorithm can be selected automatic. If tracking system is working in detecting mode and target is detected, then system will turn to tracking mode If system is working in tracking mode and target is lost, then system will turn into detecting mode. As the ADSP-21060 offers powerful features to multi-processing DSP systems, it is easy to expand to multi subordinate DSP system. It is possible to use more complexes detecting or tracing algorithms in real time tracing system.

关键词： image processing Kalman filtering segmentation tracking algorithm

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Proceedings of the 33rd SICE Annual conference (SICE'94)

Proceedings of the 33rd SICE Annual Conference (SICE'94)

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Proceedings of the 33rd SICE Annual conference (SICE'94)

The proceedings contains 64 papers. Some of the topics discussed are: control systems;vision;measurements;speed control;diesel engines;systems stability;rocket motors;induction motors;neural networks;fuzzy sets;learning systems;artificial intelligence;Petri nets;signal processing;quantum mechanical systems;parameter estimation;identification;recursive algorithms;robotics;intelligent manipulators;pattern recognition;example-based feature extraction;voice recognition;precision measurement;image distortion;atomic microscopes;bio-systems;electrocardiography;electromyography;cardiology;cardiovascular system;echocardiogram;industrial applications;multistage diagnosis;and stock prices forecasting.

关键词： Control systems

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