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检索条件"任意字段=2nd International Conference on Algorithm, Image Processing and Machine Vision, AIPMV 2024"

共 318 条记录，以下是91-100 订阅

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A vision-like network for low-light image enhancement 2

A vision-like network for low-light image enhancement

引用

2nd international conference on image processing, Computer vision and machine Learning, ICICML 2023

作者： Huang, Zishen Li, Jindong Hu, Xiao Ji, Guangyi Guangzhou University School of Mechanical and Electrical Engineering Guangzhou China

ISBN: (纸本)9798350331417

Zero-shot learning is a popular strategy for low-light image enhancement, as it allows convolutional neural networks (CNNs) to be trained without paired data. However, existing zero-shot learning methods often lead to the loss of image details and noise amplification when processing images with extremely low illumination. To address this issue, a vision-like network is proposed, which is inspired by the human visual mechanism of "first the whole, then the part". This lightweight network has only 5349 parameters and is capable of retaining image details. Additionally, a non-reference loss function based on the median filtering algorithm is proposed to reduce information loss caused by rigid denoising. Experimental results show that our method outperforms existing zero-shot learning methods. © 2023 IEEE.

关键词： curve estimation low-light image enhancement noise suppression zero-shot learning

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A Comprehensive Study of Plant Disease Detection Through image processing and machine Learning 2

A Comprehensive Study of Plant Disease Detection Through Ima...

引用

2nd IEEE international conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Pachori, Madan Kant, Shashi Surya, Anupma Kumar, Manish Greater Noida Institute of Technology Computer Science and Engineering Greater Noida India Sharda University Computer Science and Engineering Greater Noida India JECRC University Computer Science and Engineering Jaipur India

ISBN: (纸本)9798350368109

Agriculturalists can greatly benefit from techniques that forecast the kinds of illnesses that plants will encounter during their lives. This article provides information on these methods through a thorough survey that included a range of image-based plant leaf diseases. These illnesses often cause great harm and can affect any section of the plant. These illnesses cause enormous cumulative losses that lower output and raise financial losses in agriculture. The agriculture sector must persevere through these challenges and grow as a result to be very lucrative. This study examined the diagnosis of plant diseases using machine learning algorithms and general image processing methods that may be applied at various stages of a plant's life cycle. Numerous techniques based on automation or computer vision concepts are currently in place for identifying plant diseases. However, they lack precision and are hard to interpret. Furthermore, no single method can detect all conditions. For cultivation to be effective, the plant's status must be monitored at every growth stage. © 2024 IEEE.

关键词： Adversarial machine learning

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Fast 3D Object Segmentation Using DBSCAN Clustering Based on Supervoxel 2

Fast 3D Object Segmentation Using DBSCAN Clustering Based on...

引用

2nd international conference on Signal image processing and Communication, ICSIPC 2022

作者： Yao, Tuo Yang, Qinghua Zhang, Rui School of Mechanical Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9781510657694

For visual perception of indoor mobile robots, real-time segmentation of 3D objects is a very challenging problem. Due to the complexity and disorder of indoor point cloud data, many methods have been proposed to improve the segmentation accuracy, which most of them cannot meet the requirement of rapidity. Therefore, this paper proposes a method for fast segmentation of 3D point clouds based on supervoxel density clustering. First, the ground under the indoor scene is removed by using plane fitting algorithm and the point cloud data after ground removal is denoised at the same time. Then, the target object is over-segmented to obtain the supervoxels with local geometric features. The core points of the nearest neighbors at the center of the supervoxels are searched out using the kdtree indexing acceleration. Finally, the density clustering of the supervoxels is performed based on the core point density up to. Experimental results on publicly available datasets show that our proposed method can effectively improve the speed of the algorithm while ensuring accuracy. © 2022 SPIE.

关键词： Clouds image segmentation Detection and tracking algorithms 3D acquisition 3D vision Data modeling Data processing machine learning Visualization Voltage controlled current source

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Multi-Class Abnormal Behavior Detection algorithm Based on YOLOv9

Multi-Class Abnormal Behavior Detection Algorithm Based on Y...

引用

algorithm, image processing and machine vision (aipmv), international conference on

作者： Baixuan Han Yueping Peng Hexiang Hao Wenchao Kang Xuekai Zhang School of Information Engineering Engineering University of PAP Xi'an China

ISBN: (数字)9798350390254

ISBN: (纸本)9798350390261

Aiming at the shortage of accuracy and feature extraction ability of aerial image behavior detection algorithm, we designed an improved YOLOv9 multi-class abnormal behavior detection algorithm. Use drones to take aerial photos and build abnormal behavior data sets; The dimensional awareness selective integration module DASI was used to improve the detection accuracy of the model and the feature extraction ability of the self- built data set. A new general inverted bottleneck module is added at the end of the model trunk to improve the model inference efficiency. The results show that compared with the original network, the detection accuracy is increased from 90.9% to 92.6%, and the model reasoning speed is reduced from 266.2GFLOPS to 258.0GFLOPS, which improves the computing efficiency of the model and meets the requirement of high precision detection.

关键词： Accuracy Computational modeling machine vision Feature extraction Data models Cognition Detection algorithms Drones

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A Monocular vision-based Method for In-plane Moving Target Positioning and Pose Determination

A Monocular Vision-based Method for In-plane Moving Target P...

引用

algorithm, image processing and machine vision (aipmv), international conference on

作者： Chenyang Yue Rui Cao Zhixiang Zhang Boyu Liu Binbin Wang Faxin Li Northwest Institute of Nuclear Technology Xi'an Luoyang China

ISBN: (数字)9798350390254

ISBN: (纸本)9798350390261

Monocular vision is a powerful method for determining the spatial position and pose of a target object. When the target trajectory is situated within the plane, we propose an approach based on monocular vision to characterize an in-plane moving target, transforming the matter into a line-plane intersection. According to the established error analysis model, the optimal observation angle (including the angle between the camera optical axis and plane) was 90°, and the analysis results verified the theoretical feasibility of our method. Simulated experiments were conducted to evaluate the accuracy of the algorithm. Compared with traditional binocular vision, the results show that the proposed method is superior in calculating the position, velocity, and pose of the in-plane moving target. The designed experiments exhibit an equivalent level of measurement accuracy.

关键词： Analytical models Accuracy Error analysis machine vision Optical imaging Cameras Robustness Adaptive optics Trajectory Velocity measurement

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Mixed algorithm Real Time image processing for Robotic Drones in Deterministic Environments 2

Mixed Algorithm Real Time Image Processing for Robotic Drone...

引用

2nd international conference on Emerging Trends in Information Technology and Engineering, ic-ETITE 2024

作者： Soni, Kirtik Palanivelan, M. Rajalakshmi Engineering College Department of Ece Chennai India

ISBN: (纸本)9798350328202

This paper presents a mixed algorithm approach for real-time image processing on air and land based robotic drones that operate in highly deterministic environments such as automated warehouses. A combination of heuristic, multi state algorithmic solution based on Canny Edge and a CNN deep learning-based solution is proposed to ensure maximum performance out of low power embedded hardware. A heuristic i.e., rule-based approach is used for fixed, simple tasks such as navigation, docking, charging, identifying racks etc. On detecting an edge case or an anomaly beyond the scope of heuristics, the program switches to a deep learning-based approach in real time for extracting context and navigating the complex scenario. This computationally intense mode only lasts for short bursts and switches back to an appropriate, power efficient algorithm. The paper aims to study the effects of different embedded computer vision methodologies taking into account the context switching time and their effect on the computational resources such as CPU, RAM and ROM along with variations in CPU temperature and verify the effectiveness of a mixed algorithm approach on a Raspberry Pi 4 single board computer running 'Raspbian Bookworm' a 64bit Debian based operating system interfaced with a CSI Camera for visual feed. © 2024 IEEE.

关键词： Drones

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2nd IEEE international conference on Advances in Information Technology, ICAIT 2024 - Proceedings

2nd IEEE International Conference on Advances in Information...

引用

2nd IEEE international conference on Advances in Information Technology, ICAIT 2024

ISBN: (纸本)9798350383867

The proceedings contain 352 papers. The topics discussed include: PAVED: a fusion of deep reinforcement learning with biometric authentication for self-driving vehicles;exploring cutting-edge machine learning and data mining techniques for enhancing big data management with advanced algorithmic strategies for optimal data processing and analysis;interactive delta bot with voice recognition and image processing – a review;smart surveillance camera using AI;minimized computational time in cloud using advanced encryption standard algorithm over file changed with security;Kannada legal document summarizer: a survey;synergistic revolution with AI-enabled organ matching and blockchain security in transplantation management;utilizing YoLov8 architecture for sharp-edge segmentation;and learning-based super-resolution for image upscaling using sparse representation.

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Conditional Diffusion Model for image Steganography

Conditional Diffusion Model for Image Steganography

引用

algorithm, image processing and machine vision (aipmv), international conference on

作者： Hongjun Fan Ziping Zhao Wei Xia School of Computer and Information Engineering Tianjin Normal University Tianjin China

ISBN: (数字)9798350390254

ISBN: (纸本)9798350390261

To ensure robust, high-capacity, and secure communication, we propose a conditional diffusion model for coverless image steganography, called CDIS, which not only generates realistic stego images but also successfully extracts valid secret images in the case of distorted stego images. CDIS utilizes the DDIM inversion technique to achieve the transformation between images, ensuring the reversibility of steganography. Additionally, an image encoder is also used to learn the high-level semantics of the secret image and the stego image, thus speeding up the diffusion and generation process in a controlled manner. The data sampled by the latent semantics module follows the same probability distribution as the high-level semantics of real images, serving as a condition for generating the stego image, thus realizing steganography without embedding. We conduct comprehensive experiments to demonstrate the advantages of our proposed CDIS framework in terms of robustness and security.

关键词： Steganography machine vision Semantics Process control Diffusion processes Diffusion models Information retrieval Robustness Probability distribution Security

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Binarization of Documents with complex Backgrounds

Binarization of Documents with complex Backgrounds

引用

2nd international conference on machine vision

作者： Rao, A. Venkata Srinivasa Sreenivasu, Tinnathi Rao, Nekkanti Venkata Sastry, A. S. C. S. Reddy, L. Pratap Prabhu, T. S. Krishna SVEC ECE Dept Tadepalligudem Andhra Pradesh India JNTU Hyderabad Dept ECE Hyderabad Andhra Pradesh India TCS Hyderabad Hyderabad Andhra Pradesh India

ISBN: (纸本)9780769539447

In this paper, a novel heuristic based approach adopted from *** algorithm for removing background noise from all types of images with complex background is presented. In this approach Binarization is done by selecting two threshold values, one for foreground and another for background for the separation. Morphological techniques are used for improving the quality of the resultant image. In addition to this PSNR ratio is calculated for all the images and its variation with respect to the intensity of the background noise is observed.

关键词： Binarization Document image processing Document with complex background

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Performance Improvement in Welding Operations Through image processing 2

Performance Improvement in Welding Operations Through Image ...

引用

2nd international conference on Artificial Intelligence and machine Learning Applications, AIMLA 2024

作者： Sharma, Mohit Kumar Menon, Soumya V Tripathy, Padmaja Vivekananda Global University Department of Electrical Engineering Jaipur India School of Sciences Department of Chemistry and Biochemistry Karnataka Bangalore India ARKA JAIN University Department of Mechnical Engineering Jharkhand Jamshedpur India

ISBN: (纸本)9798350349221

This examination intends to enhance the overall performance of welding operations through picture processing. It's going to use an aggregate of PC vision and gadgets, getting to know to perceive better and tune welds, improve the accuracy of the system, and reduce the capability for mistakes. Particularly, the study will make use of a deep learning method to classify welds in specific classes, allowing the welding operations to be more effectively monitored and operated. Additionally, a convolutional neural network technique will be utilized to pick out the welds and estimate the vital parameters from the image statistics. Sooner or later, a robot arm geared up with a digital camera and a torch can be used to validate the welding process in an actual-world scenario. The effects of this take a look at will be used to enhance the performance and nice of welding operations through higher visibility into the system. © 2024 IEEE.

关键词： Welds

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