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

共 16444 条记录，以下是1481-1490 订阅

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Fire Incendie Detection A compartive study of Convolutional Neural Networks (CNN) and Support Vector Machines (SVM).

Fire Incendie Detection A compartive study of Convolutional ...

引用

International conference on image and Signal processing and their Applications (ISPA)

作者： Yasmine Guerbai Asma Saibi Department of Electrical Systems Engineering M‘Hammed Bougara University Boumerdès Boumerdès Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

In recent years, the application of artificial intelligence (AI) techniques for fire detection has gained significant attention due to its potential for enhancing early fire detection systems. This study aims to compare the performance of deep learning convolutional neural networks (CNN) and support vector machine (SVM) machine learning algorithms in the context of fire detection. We present a comprehensive analysis and evaluation of the two approaches, highlighting their strengths and weaknesses, and discussing their potential for real-world fire detection applications.

关键词： Support vector machines Deep learning Machine learning algorithms Neural networks Signal processing Vectors Convolutional neural networks

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Joint Optimization of Trajectory and image Transmission in Multi-UAV Semantic Communication Networks 29

Joint Optimization of Trajectory and Image Transmission in M...

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29th IEEE International conference on Parallel and Distributed systems, ICPADS 2023

作者： Yao, xiancai Zheng, Jianchao Zheng, xin Dai, Huadong Yang, xiaolong Academy of Military Science of PLA Beijing100071 China Beijing100071 China

ISBN: (纸本)9798350330717

Semantic communication is considered the key promoter and basic paradigm of future 6G networks and applications. In this paper, we investigate a multi-unmanned aerial vehicle (UAV) semantic communication framework, where the trajectories and communication services are jointly optimized for image transmission of ground users. We aim to minimize the transmission delay while considering constraints such as the UAV's energy threshold, collision avoidance, and the bandwidth of the multi-UAV system. We propose a value decomposition based multi-agent deep reinforcement learning (VD-MADRL) algorithm to solve this problem, which explores the joint optimization scheme of UAV trajectory, channel allocation, and semantic information selection. Simulations demonstrate that the proposed algorithm greatly reduces system energy consumption and transmission delay compared to other traditional UAVs' trajectory planning algorithms. © 2023 IEEE.

关键词： joint optimization multi-agent Deep Reinforcement Learning Multi-UAV semantic communication

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A Real-Time Aerial imagery Collection, Mapping, and Remote Sensing Testbench for Uncrewed Missions

A Real-Time Aerial Imagery Collection, Mapping, and Remote S...

引用

International conference on Unmanned Aircraft systems (ICUAS)

作者： Calvin Coopmans Richard Snider Sadikul Alim Toki Andres Sewell Steve Petruzza Emma Montgomery Department of Electrical and Computer Engineering Utah State University Logan UT USA Department of Computer Science Utah State University Logan UT USA

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

As uncrewed aerial systems continue to grow in popularity and importance, the long-term and scalable use of these systems for remote sensing and imagery data collection remains a valuable and achievable goal. To enable these systems at scale, real-time onboard imagery processing is required. To determine the feasibility of real-time remote sensing systems, many factors must be accounted for, including the ability of the sensing and processing algorithms to operate on and collect data from real-world scenes and deliver actionable intelligence to the data consumer. In this paper, a holistic simulation system based on ROS 2 and Gazebo is presented, which allows for real-time processing algorithms to be tested and proven for flight in an accurate and extensible way. By using ROS 2 and USU AggieAir's STARDOS platform, it is possible to show how the remote sensing system and onboard, real-time processing algorithms are applicable to the aerial remote sensing task (i.e. it can demonstrate feasibility for physical deployment based on accurate simulated data processing).

关键词： Accuracy Codes Data collection Autonomous aerial vehicles Real-time systems Software Hardware Sensors Remote sensing image stitching

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image processing Using Elephant Herding Optimization: A Review 1

引用

2nd International conference on Intelligent Computing Techniques for Smart Energy systems, ICTSES 2021

作者： Soni, Vishnu Sharma, Abhay Rajpurohit, Jitendra Amity University Rajasthan Jaipur India University of Petroleum and Energy Studies Dehradun India

ISBN: (数字)9789811902529

ISBN: (纸本)9789811902512

Nature-inspired algorithms (NIAs) are very well defined for intuitive image processing operations. Among various nature-inspired algorithms, elephant herding optimization (EHO) is most preferably used as its application in image segmentation due to its high accuracy, efficient and optimized output, optimal to high speed, excellent performance, and ability of solve multi-objective optimization problems. This paper presents a review of various articles on EHO for image segmentation. For this purpose, recent development in the field of image segmentation and optimized results has been studied, and their outcomes have been presented. image segmentation, edge-based segmentation, thresholding, region-based segmentation, and morphological segmentation by mean of EHO are studied and presented with optimized outcomes. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Morphology

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Performance optimization of Histogram Equalization for digital images using modern imaging

Performance optimization of Histogram Equalization for digit...

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International conference on Computing and Networking Technology (ICCNT)

作者： G Kalyan Kumar Anita Titus R.S. Vijayashanthi M Shalini M Dinesh Department of CSE Rajalakshmi Institute of Technology Chennai Department of ECE Jeppiaar University Chennai Department of ECE S.A. Engineering College Chennai Department of CSE St. Joseph’s College of Engineering Chennai Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Saveetha University Chennai

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Histogram equalization is a method of contrast adjustment in image processing using the image’s histogram. However, as modern imaging systems become more complex, these traditional algorithms for histogram equalization are no longer efficient. In response to this problem, researchers have studied several strategies for improving the performance of histogram equalization in digital images. An option is to use parallel processing and multi-threading approaches to distribute the computational burden, thereby speeding up the execution of histogram equalization. Another methodology includes using machine learning algorithms to adapt histogram equalization parameters according to the input image. Furthermore, using advanced hardware architectures like Field Programmable Gate Arrays (FPGA), Graphic processing Units (GPU), or Application Specific Integrated Circuits can significantly enhance the speed and efficiency of a Histogram Equalization. The performance optimization techniques have provided encouraging results, which significantly refine image processing time and visual perception. Modern imaging systems may benefit tremendously from their use in the new age.

关键词： Histograms Machine learning algorithms Digital images Surveillance Graphics processing units Parallel processing Real-time systems Optimization Field programmable gate arrays Visual perception

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A Modern C++ Point of View of Programming in image processing 2022

A Modern C++ Point of View of Programming in Image Processin...

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21st ACM SIGPLAN International conference on Generative Programming: Concepts and Experiences, GPCE 2022, co-located with ACM SIGPLAN conference on systems, Programming, Languages, and Applications, SPLASH 2022

作者： Roynard, Michaël Carlinet, Edwin Géraud, Thierry EPITA Research Laboratory Le Kremlin-Bicetre France

ISBN: (纸本)9781450399203

C++ is a multi-paradigm language that enables the programmer to set up efficient image processing algorithms easily. This language strength comes from many aspects. C++ is high-level, so this enables developing powerful abstractions and mixing different programming styles to ease the development. At the same time, C++ is low-level and can fully take advantage of the hardware to deliver the best performance. It is also very portable and highly compatible which allows algorithms to be called from high-level, fast-prototyping languages such as Python or Matlab. One fundamental aspects where C++ shines is generic programming. Generic programming makes it possible to develop and reuse bricks of software on objects (images) of different natures (types) without performance loss. Nevertheless, conciliating genericity, efficiency, and simplicity at the same time is not trivial. Modern C++ (post-2011) has brought new features that made it simpler and more powerful. In this paper, we focus on some C++20 aspects of generic programming: ranges, views, and concepts, and see how they extend to images to ease the development of generic image algorithms while lowering the computation time. © 2022 ACM.

关键词： MATLAB

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Low-Illumination Lane Detection by Fusion of Multi-light Information

Low-Illumination Lane Detection by Fusion of Multi-light Inf...

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IEEE International conference on Multisensor Fusion and Integration for Intelligent systems (MFI)

作者： Zhao, Wenbo Tian, Wei Han, Yi Yu, xianwang Tongji Univ Sch Automot Studies Shanghai 201804 Peoples R China

ISBN: (数字)9781665460262

ISBN: (纸本)9781665460262

Lane detection based on the visual sensor is of great significance for the environmental perception of the intelligent vehicle. Current mature lane detection algorithms are trained and implemented in good visual conditions. However, the low-light environment such as in the night is much more complex, easily causing misdetections and even perception failures, which are harmful to the downstream tasks such as behavior decision and control of ego-vehicle. To tackle this problem, we propose a new lane detection algorithm that introduces the multi-light information into lane detection task. The proposed algorithm adopts a multi-exposure image processing module, which generates and fuses multi-exposure information from the source image data. By integrating this module, mainstream lane detection models can jointly learn the extraction of lane features as well as the enhancement of low-exposed image, thus improving both the performance and robustness of lane detection in the night.

关键词： lane detection image enhancement multi-exposure fusion

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Integrating the dynamic optimization strategies of Adam and AdaGrad

Integrating the dynamic optimization strategies of Adam and ...

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International conference on Intelligent Control and Information processing (ICICIP)

作者： Zhixuan Huang xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798331516147

ISBN: (纸本)9798331516154

Artificial intelligence (AI) has been a key research area since the 1950s, initially focused on using logic and reasoning to create systems that understand language, control robots, and offer expert advice. With the rise of big data and deep learning, AI has advanced in applications like recommendation systems, image recognition, and machine translation, primarily through optimizing loss functions in deep neural networks to improve accuracy and reduce training *** descent is the core optimization method but faces challenges like slow convergence and local minima. To overcome these, algorithms like Momentum, AdaGrad, RMSProp, Adadelta, Adam, and Nadam have been developed, introducing momentum and adaptive learning rates to accelerate convergence. This paper presents a new optimization algorithm that combines the strengths of Adam and AdaGrad, offering better adaptability to different learning rates.

关键词： Training Heuristic algorithms Optimization methods Machine translation Logic Artificial intelligence Robots Recommender systems Convergence Intelligent control

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A Method of Dual-spectrum Feature Fusion for Face Recognition Under Non-ideal Lighting Conditions 22

A Method of Dual-spectrum Feature Fusion for Face Recognitio...

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4th International Symposium on Signal processing systems, SSPS 2022

作者： Ai, Da Fan, Weixin Jia, Kai Lu, Mingyue Liu, Ying Center for Image and Information Processing Xi'an University of Posts and Telecommunications Shaanxi Xi'an China School of Communication and Information Engineering Xi'an University of Posts and Telecommunications Shaanxi Xi'an China

ISBN: (纸本)9781450396103

Face recognition technology is widely used in the field of public security. To improve the recognition accuracy under non-ideal lighting conditions, a face recognition method with dual-spectrum feature fusion is proposed using the property that the infrared spectrum is insensitive to visible light. The fused face images of visible and near-infrared spectra are obtained with the Non-Subsampled Shearlet Transform (NSST) algorithm, and then been put into the FaceNet as input and trained using transfer learning to renew the FaceNet model parameters for recognizing the fused face images. Compared with existing methods, experimental results show that the accuracy of face recognition is significantly improved under non-ideal lighting conditions which better meets the practical application requirements of public security. © 2022 ACM.

关键词： Face recognition

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image processing-Based Presentation Control System Using Binary Logic Technique 1st

Image Processing-Based Presentation Control System Using Bin...

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1st International conference on Expert Clouds and Applications, ICOECA 2023

作者： Chinchmalatpure, Sheela Ingale, Harshal Jadhao, Rushikesh Ghule, Ojasvi Ingole, Madhura Vishwakarma Institute of Technology Maharashtra Pune411037 India

ISBN: (纸本)9789819917440

Providing a perfect presentation becomes a challenging job because of various factors like changing the slides and the correct keys to be used to change the slides while maintaining composure in front of the audience. There are a lot of interruptions during a presentation when using the keyboard for controlling the slides. Therefore, this paper proposes a smart presentation system using hand gestures which provides an easy way to change or operate the slides. The proposed system uses various algorithms to detect different hand gestures to perform several operations. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Python

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