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

共 12976 条记录，以下是1011-1020 订阅

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Two-Archive-Based Competitive Swarm Optimizer for Constrained Multiobjective Optimization 5

Two-Archive-Based Competitive Swarm Optimizer for Constraine...

引用

5th International conference on Data-Driven Optimization of Complex systems, DOCS 2023

作者： Li, Lianghao He, Cheng Lin, Jianqing Pan, Linqiang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China Wuhan China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350393521

Constrained multiobjective optimization problems (CMOPs) are prevalent in various real-world applications, presenting a formidable challenge to existing evolutionary algorithms when faced with intricate constraints. When solving CMOPs, a crucial concern is achieving a balance between convergence, diversity, and feasibility. To address these challenges, this paper proposes a two-archive-based constrained multiobjective competitive swarm optimizer. The algorithm preserves two collaborative and complementary archives to improve population convergence and feasibility. By implementing a competitive particle swarm mechanism, offspring solutions are generated by drawing upon solutions from both archives, thus capitalizing on their synergistic effect and exceptional information. An adaptive parameter is also used to adjust the bias in choosing the winner in the paired competition during the evolution. The experimental results demonstrate the effectiveness of the proposed algorithm in handling constrained multiobjective optimization problems. © 2023 IEEE.

关键词： Constraint handling

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image Registration for Virtual Drone Flight Simulation

Image Registration for Virtual Drone Flight Simulation

引用

2023 IEEE International conference on Electrical, Computer and Energy Technologies, ICECET 2023

作者： Koniarski, Konrad Myśliński, Andrzej Systems Research Institute Polish Academy of Sciences ul. Newelska 6 Warsaw01-447 Poland

ISBN: (纸本)9798350327816

In the past decade, drones have expanded their applications, such as surveying, search and rescue, and last-mile delivery. Drone autonomy is a growing focus in these areas, requiring test environments for both drone operators and autonomous algorithms. This work addresses the creation of a realistic test environment for accurate position perception, motion planning, and drone control. Our approach uses RGB-D sensors and image registration techniques to construct a 3D map of the real environment, enabling drone navigation simulation. We adapt the Iterative Closest Point (ICP) algorithm, incorporating feature point filtering and local optical flow to expedite 3D point processing, particularly in static scenes. A challenge in the standard ICP algorithm is selecting suitable initial points for effective matching between consecutive point clouds. Our modified approach tackles this issue, optimizing the algorithm for 3D map construction. Since our application involves RGB-D image sequences with minimal variation between successive key frames, we use a scale-space pyramid and FAST techniques to select a limited number of key points, reducing the computational load. Moreover, by employing a local optical flow-based point-matching approach, we eliminate resource-intensive operations in each ICP optimization iteration. We demonstrate the practical utility of our method through a virtual 3D drone flight simulator. © 2023 IEEE.

关键词： drone operation simulation ICP registration structure from motion

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A Parallel and Asynchronous Blob Shape Descriptor Implemented in CMOS Technology 33

A Parallel and Asynchronous Blob Shape Descriptor Implemente...

引用

33rd IEEE International conference on Microelectronics, MIEL 2023

作者： Bogacki, P. Dlugosz, M. Talaska, T. Dlugosz, R. Aptiv Services Poland Kraków30-399 Poland Agh University of Science and Technology Institute of Telecommunications Faculty of Computer Science Electronics and Telecommunications Kraków30-059 Poland Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350347760

The paper presents a family of novel light blob shape descriptors for use in selected active safety algorithms used in Advanced Driver Assistance systems (ADAS). One of the motivations was to obtain a descriptor that would ensure low computational complexity. This makes it easy to implement both in software and hardware. One assumption is that the location of the center of a given light spot is approximately known. The principle of its operation is then to count white pixels in selected directions, starting from this central point. A key issue here is an efficient way of determining indexes of particular pixels belonging to the image patch, as well as the location of points representing places where the white area turns into black. In the case of a hardware implementation, this can be done using a parallel circuit operating in asynchronous mode, without the need for a control clock. © 2023 IEEE.

关键词： Pixels

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Status of the Automated Data Extraction, processing, and Tracking System (ADEPTS) for CHARIS/SCExAO 7

Status of the Automated Data Extraction, Processing, and Tra...

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conference on Software and Cyberinfrastructure for Astronomy vii

作者： Tobin, Taylor L. Pal, Jonathan Chilcote, Jeffrey Brandt, Timothy Currie, Thayne Groff, Tyler Lozi, Julien Guyon, Olivier Univ Notre Dame Dept Phys Nieuwland Sci Hall Notre Dame IN 46556 USA Univ Calif Santa Barbara Phys Dept Broida Hall Santa Barbara CA 93106 USA Univ Texas San Antonio Dept Phys & Astron 1 UTSA Circle San Antonio TX USA Natl Astron Observ Japan Subaru Telescope 650 North Aohoku Pl Hilo HI USA NASA Goddard Space Flight Ctr Greenbelt MD USA Univ Arizona Steward Observ Tucson AZ USA Univ Arizona Coll Opt Sci Tucson AZ USA Astrobiol Ctr NINS 2-21-1 Osawa Mitaka Tokyo Japan

ISBN: (纸本)9781510653603;9781510653597

CHARTS is a near-infrared (JHK) coronagraphic integral field spectrograph (IFS) housed on the Subaru Telescope. In conjunction with the extreme adaptive optics system, SCExAO, it provides high-contrast spectral imaging of substellar companions and circumstellar disks. However, data extraction, calibration, and processing are time consuming processes with a steep learning curve, creating a bottleneck and slowing the production of scientific results. The new Automated Data Extraction, processing, and Tracking System (ADEPTS) will automatically process all data taken by CHARTS, building calibration files and extracting science-grade data cubes, as well as performing post-processing on the results using default parameters. ADEPTS also serves as a backend for CHARTS in terms of file organization, logging all raw and produced files in a searchable SQLite database and providing a mechanism for user flagging of bad files. By using automation to remove wait times and reducing elapsed computation time via parallelization on its home 72-CPU processor, ADEPTS will be able to produce science-grade data products within a day of observations. We present an update on the current status of ADEPTS, as well as new features and design modifications.

关键词： SCExAO CHARTS ADEPTS Data management image processing Databases Software development Data archive systems

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Novel Development of an Obstacle Avoidance Algorithm Development for a Mobile Robotic Vehicle 15

Novel Development of an Obstacle Avoidance Algorithm Develop...

引用

15th International conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Bharadwaj, Adtiya A. Dhanwin, H. Srinivas, K. Sudeep, S.R. Gowda, Suprith G. Pavithra, G. Manjunath, T.C. VII Sem Electronics & Communication Engineering Dayananda Sagar College of Engineering Karnataka Bangalore India Dept. of Electronics & Communication Engineering Dayananda Sagar College of Engineering Karnataka Bangalore India

ISBN: (纸本)9798331300579

The research work presented in this paper gives a comprehensive approach to the design and implementation of an innovative obstacle avoidance algorithm tailored for mobile robotic vehicles. The primary aim is to develop a robust system capable of effectively detecting and navigating around obstacles in real-time scenarios. The algorithm is constructed using MATLAB, leveraging its computational capabilities and extensive toolset for algorithm development and simulation. The methodology encompasses several key stages. Initially, sensor data acquisition is performed through various sensors integrated into the robotic platform, including but not limited to cameras, LiDAR, ultrasonic sensors, or a combination thereof. Subsequently, a systematic and multi-faceted approach is employed for obstacle detection, involving techniques such as image processing, depth perception, and sensor fusion. The detected obstacle information is then processed and integrated to generate a dynamic and adaptable avoidance strategy. This strategy accounts for the vehicle's kinematics, environmental constraints, and real-time feedback, allowing for agile and safe navigation in complex and dynamic environments. The algorithm's responsiveness is optimized through iterative testing and refinement, ensuring its reliability and efficiency in diverse scenarios. The algorithm's performance is evaluated through extensive simulation studies and practical experiments with the mobile robotic platform operating in controlled and real-world environments. Quantitative metrics, including obstacle detection accuracy, avoidance efficiency, and computational performance, are employed to assess and validate the algorithm's effectiveness. The outcomes of this research contribute to the advancement of obstacle avoidance methodologies for mobile robotics, offering insights into the development of adaptive and intelligent systems capable of navigating challenging terrains autonomously. The proposed algorithm demonstra

关键词： Obstacle detectors

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Fast Convergence and Low Complexity Algorithm for Multichannel Adaptive Filtering

Fast Convergence and Low Complexity Algorithm for Multichann...

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Telecommunications and Intelligent systems (ICTIS), International conference on

作者： Mohamed Zerouali Mohamed Djendi Signal Processing and Image Laboratory (LATSI) University of BLIDA 1 Blida Algeria

ISBN: (数字)9798331527396

ISBN: (纸本)9798331527402

In this research, we propose a new multi-channel adaptive filtering method with low complexity and optimized convergence rate. The basic strategy behind the proposed algorithm is to generalize the decorrelation technique used in FNLMS algorithm to the multi-channel case by estimating the prediction parameters for each channel to decorrelate the multi-channel input signals. In simulation we confirm the high performances of the proposed algorithm with comparison of the two dimensions multi-channel Affine Projection (multi-channel APA) and the multi-channel Normalized Least Mean Square (multi-channel NLMS) algorithms.

关键词： Adaptive systems Echo cancellers Filtering Filtering algorithms Prediction algorithms Decorrelation Complexity theory Telecommunications Intelligent systems Convergence

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Automatic Segmentation of Rectal Tumor on Magnetic Resonance images via a Deep Discriminative Model Consisting of Asymmetric U-Net and Convolutional Conditional Random Field based Post-processing 19

Automatic Segmentation of Rectal Tumor on Magnetic Resonance...

引用

19th International conference on Natural Computation, Fuzzy systems and Knowledge Discovery, ICNC-FSKD 2023

作者： Li, Xing Chen, Hao Ge, Sisi Xi'an University of Posts and Telecommunications School of Computer Science Xi'an710121 China Xi'an University of Posts and Telecommunications School of Humanities and Foreign Languages Xi'an710121 China

ISBN: (纸本)9798350304398

The process of manual delineating is frequently time-consuming and can result in low consistency. Our goal was to design a deep discriminative model (DDM) to mitigate these issues of magnetic resonance imaging (MRI) for rectal tumor lesion boundary delineation, and we proposed an asymmetric U-Net rectal tumor MR images segmentation algorithm based on multi-scale dilated convolutional inputs and convolutional conditional random fields (ConvCRFs). A multiscale convolutional input module was designed as a preprocessing step to enrich the extraction and input of global contextual semantic information;then, an asymmetric U-Net network combined with ConvCRFs was used to discriminatively fine-tune the segmentation results so as to enhance segmentation accuracy of tumors. To verify the feasibility of the algorithm, the experiments were conducted on a private dataset provided by a medical institution, and the experimental Dice coefficient reached 0.876 on T2WI images, 0.851 on DWI images, respectively, indicating the existence of an important clinical guidance value for rectal tumor image segmentation algorithms. © 2023 IEEE.

关键词： Tumors

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Robust Calibration for Enhanced Imaging in Near-Field D-Band MIMO Radar systems

Robust Calibration for Enhanced Imaging in Near-Field D-Band...

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European conference on Antennas and Propagation, EuCAP

作者： Lorena Perez-Eijo Marcos Arias Borja Gonzalez-Valdes José Vázquez-Cabo Ignacio Sardinero–Meirás Jesus Grajal AtlanTTic Research Center Universidade de Vigo Vigo Spain Information Processing and Telecommunications Center Universidad Politécnica de Madrid Madrid Spain

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This work introduces a calibration algorithm designed to improve high-precision imaging in real-time MIMO radar systems. The algorithm applies the Inverse Fourier Transform (IFFT) and advanced signal processing techniques to efficiently extract and process key data from raw measurements, focusing on critical Regions Of Interest (ROI) while filtering out unnecessary information. A robust phase correction mechanism ensures precise calibration and alignment, preventing phase errors that could otherwise lower image quality. The algorithm provides an effective balance between computational efficiency and the high accuracy required by modern MIMO radars, paving the way for further improvements in real-time imaging.

关键词： MIMO radar Signal processing algorithms Coherence Radar imaging Signal processing Real-time systems Hardware Calibration Spatial resolution image reconstruction

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Research on Efficient image Feature Extraction based on Low-Rank Representation for Intelligent Reading systems

Research on Efficient Image Feature Extraction based on Low-...

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image processing, Electronics and Computers (IPEC), Asia-Pacific conference on

作者： Yulan Tan Heilongjiang University of Technology Jixi China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

Efficient and accurate extraction of image features is essential for ensuring high-performance information transmission in intelligent reading systems. This paper introduces a computer-assisted method for intelligent image feature extraction, specifically focusing on the Low-Rank Representation (LRR) approach. The study addresses challenges presented by noisy and diverse character or image data encountered in real-world scenarios. By employing LRR, the accuracy of image extraction, which includes object recognition and scene understanding, is significantly enhanced. Subsequently, the proposed techniques for intelligent image feature extraction undergo comprehensive evaluation, assessing both effectiveness and versatility through extensive experiment verifications. The experimental results validate the efficacy of the proposed method and demonstrate its superior image content extraction accuracy compared to existing methods. This proposed method provides crucial assistance to high-performance intelligent reading systems, thereby enhancing its applicability for potential consumers.

关键词： YOLO Visualization Accuracy Process control Feature extraction Rendering (computer graphics) Classification algorithms Data mining Proposals Principal component analysis

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A Cooperative Gene Regulatory Network Target Entrapping in GNSS-denied Environments 12

A Cooperative Gene Regulatory Network Target Entrapping in G...

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12th International conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Shi, Ze Fan, Zhun Ma, Peili Hong, Juncao Li, Wenji Zhu, Guijie Huang, Huaxing Cai, Yuwei Dong, Zhaohui Zhu, Xiaomin Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou515063 China College of Systems Engineering National University of Defense Technology China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In recent years, the use of gene regulatory network (GRN) to guide swarm robots for target-entrapping tasks has received increasing attention. Even though many GRN-based algorithms for swarm aggregation morphogenesis generation are designed and verified in two-dimensional space, they are not suit-able for target trapping in three-dimensional space with GNSS-denied environments. Therefore, we propose a cooperative GRN (Co-GRN), which can guide swarm robots to complete target-entrapping tasks in GNSS-denied three-dimensional environments. The average distance and enveloping strength are analysed in several simulated scenes, and the effectiveness and flexibility of the proposed method are verified. © 2022 IEEE.

关键词： Genes

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