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检索条件"任意字段=Image Processing: Machine Vision Applications"

共 6572 条记录，以下是1171-1180 订阅

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Non-Linear Time Sequence Problems Based on GA-BP Neural Network Prediction Model

Non-Linear Time Sequence Problems Based on GA-BP Neural Netw...

引用

image processing and Computer applications (ICIPCA), IEEE International Conference on

作者： Teng Wang Yuxuan Chen College of Technology and Data Yantai Nanshan University Yantai China School of Software Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

In the fields of image recognition and computer vision, data mining and predictive analytics, BP neural network as a kind of simple structure and powerful model has been widely concerned by scholars, and the improvement of BP neural network is very important. In this paper, we used genetic algorithm to optimize BP neural network, and optimize the selection of weights and thresholds of BP neural network through the characteristics of local optimization of genetic algorithm. Compared with the single BP neural network, the root mean square error (RMSE) of the optimized BP neural network had been reduced by 0.82%, the mean absolute error (MAE) had been reduced by 0.85%, and the coefficient of determination had been improved by 1.34%• The experimental results have shown that the optimization of BP neural network with genetic algorithm is more advantageous than the single BP neural network, and the optimized BP neural network has a strong ability to deal with the complex problems with high dimensions and multi-objectives.

关键词： machine learning algorithms image recognition image coding Neural networks Predictive models Genetics Root mean square Predictive analytics Optimization Genetic algorithms

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Engineering applications based on Industrial Robots and machine vision

Engineering Applications based on Industrial Robots and Mach...

引用

image processing, Computer vision and machine Learning (ICICML), International Conference on

作者： Yiren Huang Weidong Hao Zhihao Wang Hao Wu School of Mechanical and Electrical Engineering Guilin University of Electronic Technology Guilin Guangxi China

ISBN: (纸本)9781665464697

This paper introduces the structure and operation mode of automatic production line based on the actual situation of laser quenching automatic production line of tool in enterprises. Robot vision integrates workpiece positioning coordinates with robot coordinates to realize the positioning and grasping function of robot through machine vision. Focus on OpenCV image processing methods. This paper describes its principle and possible problems from the aspects of system structure, robot coordinate calibration, visual identification and positioning and software design.

关键词： Visualization Software design Service robots Shape Robot kinematics machine vision Robot vision systems

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MCDM-DTI: Accelerating Diffusion Tensor Imaging based on Multi-Conditional Denoising Diffusion Probability Model

MCDM-DTI: Accelerating Diffusion Tensor Imaging based on Mul...

引用

image processing, Computer vision and machine Learning (ICICML), International Conference on

作者： Jinling He Lang Zhang Yanjie Zhu Liang Dong Department of Mathematics and Physics Lanzhou Jiaotong University Lanzhou China Lauterbur Research Center for Biomedical Imaging Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Pharmacy and Bioengineering Chongqing University of Technology Chongqing China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Diffusion tensor imaging (DTI) is a significant non-invasive neuroimaging technique with valuable applications in clinical medicine. To address the lengthy acquisition times and high costs of traditional DTI technology, we propose a multi-conditional diffusion model for accelerated DTI (MCDM-DTI). This model generates high-quality DTI maps using only six diffusion-weighted images (DWIs) and one b0 image. The model leverages the diffusion process of Denoising Diffusion Probabilistic Models (DDPMs) to learn the underlying data distribution of DTI maps. By incorporating the DWIs and the b0 image as conditional inputs to a U-Net denoising network, MCDM-DTI produces more accurate DTI parameter maps. The introduction of Class Label Embedding technology extracts category-specific features, enabling the concurrent generation of all category parameter maps. Additionally, a binary image erosion algorithm can eliminate edge noise. Validated on the Human Connectome Project dataset (HCP), MCDM-DTI demonstrates superior performance in generating FA, MD, and AD, along with good robustness against noise, compared to previously studied methods. Our approach achieves over a 5-fold boost in imaging speed while maintaining high-resolution DTI maps, significantly reducing acquisition time.

关键词： Neuroimaging image edge detection Noise reduction Noise Diffusion processes Diffusion models Feature extraction Robustness Diffusion tensor imaging Erosion

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A Real-Time Monitoring Computer Algorithm System for Occlusion of Photovoltaic Panels Developed by machine vision Technology

A Real-Time Monitoring Computer Algorithm System for Occlusi...

引用

image processing and Computer applications (ICIPCA), IEEE International Conference on

作者： Xixing Hu Weiyan Zheng Fang Su Chaoyue Zhu Zhejiang Dayou Industrial Co. Ltd. Hangzhou Science and Technology Development Branch Hangzhou China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

In this paper, a multi-feature detection method based on graph cut for photovoltaic panels is proposed. Combined with multi-dimensional features such as optical flow field and light intensity, an interactive feature recognition method is constructed. The combination of each feature forms a pixel feature vector and is fed into a random forest classifier. The interaction information between adjacent pixel pairs is extracted. The energy function and adaptive algorithm of object-based occlusion detection are constructed. This Paper build an undirected graph. The object is segmented by the graph cutting principle. The findings from the experiments indicate that the new technique surpasses traditional methods in precision and offers enhanced responsiveness for detecting obstructions.

关键词： Photovoltaic systems Photovoltaic cells Software algorithms Real-time systems Vectors Software Monitoring Surface treatment Random forests Optical flow

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Artificial Intelligence Algorithms for Robotic Harvesting of Agricultural Produce

Artificial Intelligence Algorithms for Robotic Harvesting of...

引用

AIML-applications for Engineering & Technology (ICAET), International Conference on

作者： Nilesh R. Kolhalkar Anupama A. Pandit Shridhar Ashok Kedar G. Yedukondalu Department of Mechanical Engineering MKSSS's Cummins College of Engg. For Women Pune MH India Department of Computer Science & Engg. Defence Institute of Advanced Technology (D.I.A.T) Pune Pune MH India Department of Mechanical Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Vijayawada A.P. India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

Robotic harvesting of fruits and vegetables is an advanced technology that leverages Robotics, Artificial Intelligence, and machine vision to harvest the fruits autonomously from plants or trees. This technology aims to address labor shortages, enhance efficiency, reduce costs, and minimize damage to the fruit during harvesting. AI algorithms for fruit detection and harvesting are increasingly used in agricultural automation to improve efficiency and accuracy. The accuracy of detection algorithms in fruit detection and harvesting can differ reliant on various factors, including the type of algorithm used, the quality and diversity of the training data, the complexity of the environment, and the specific fruits being targeted. Advanced control algorithms integrated with image processing ensure that the robotic arm moves smoothly and accurately, minimizing the risk of bruising or damaging the fruit. Soft robotics and adaptive gripping technologies are discussed in the paper which can handle delicate fruits like grapes, without applying excessive force. machine vision integrated robot arm with novel gripper and cutter for harvesting cluster fruit like grapes is reported in the paper. Case studies of agricultural robots for Orchards, Greenhouses and Field Crops are discussed with detailed analysis along with challenges, future trends and innovations.

关键词： Accuracy Costs Automation machine vision Pipelines Lighting Training data Robot sensing systems Prediction algorithms Robots

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Cyclic Angle Encoding and Angle-Embedded Attention for Robust Oriented Object Detection in Remote Sensing images

Cyclic Angle Encoding and Angle-Embedded Attention for Robus...

引用

image processing, Computer vision and machine Learning (ICICML), International Conference on

作者： Yujian Wang Yi Hou Shilin Zhou College of Electronic Science and Technology National University of Defense Technology Changsha China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Rotated object detection in remote sensing images is crucial for various applications, including surveillance, urban planning, and environmental monitoring. However, this task is challenging due to the diverse orientations and scales of objects, as well as the complex background in aerial images. Traditional regression-based methods often suffer from boundary issues, leading to significant loss values and reduced detection accuracy. To address these challenges, we introduces a novel method for oriented object detection. We propose a cyclic angle encoding approach that converts angle prediction from a regression problem to a classification problem, effectively mitigating boundary issues and improving angle prediction accuracy. Additionally, we introduce an embedded angle information deformable attention mechanism to better align features with sampling points, enhancing the model's performance in rotated object detection tasks. Experiments on the DOTA-v1.0 dataset, a large-scale aerial image dataset, demonstrate the effectiveness of our method. Our approach achieves a mean average precision (mAP) of 80.98%, outperforming several state-of-the-art methods. Notably, our method achieves a precision of 90.70% in the aircraft category and shows robust performance across various categories and challenging scenarios. The proposed innovations in angle encoding and attention mechanism significantly improve detection accuracy and model robustness.

关键词： Technological innovation image coding Accuracy Attention mechanisms Atmospheric modeling Urban planning Object detection Feature extraction Robustness Remote sensing

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A vision-Based Solution for Water Level Monitoring in Flash Floods Scenario

A Vision-Based Solution for Water Level Monitoring in Flash ...

引用

IEEE Sensors applications Symposium, SAS

作者： Bruno Andò Salvatore Castorina Salvatore Graziani Dipartimento di Ingegneria Elettrica Elettronica e Informatica (DIEEI) University of Catania Catania Italy

ISBN: (数字)9798350369250

ISBN: (纸本)9798350369267

Flash floods represent a serious problem, especially in urban areas, due to the consequences of sediment transport and other phenomena affecting security and life quality of citizens. The availability of low-cost solutions for the real-time monitoring of such phenomena, with particular regards to the water level in urban areas, is of main interest for the realization of early warning systems aimed to predict and handle hazardous events. In this paper a water level monitoring system, based on a low-cost vision system and a dedicated signal processing implemented on an embedded hardware platform, is presented. Main advantage of the proposed approach resides in the adopted sensing methodology, which besides being low-cost, allows for a robust estimation of the water level, without the need for active (powered) ground devices. A proof-of-concept aimed prototype has been realized and its performances have been assessed by means of a dedicated experimental survey. Obtained results highlight high sensitivity and specificity in the water level recognition, with an accuracy close to 100% over the whole explored detection range.

关键词： image recognition Target recognition machine vision Urban areas Signal processing algorithms Prototypes Cameras

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Illumination Normalization by Partially Impossible Encoder-Decoder Cost Function

Illumination Normalization by Partially Impossible Encoder-D...

引用

IEEE Winter Conference on applications of Computer vision (WACV)

作者： Da Cruz, Steve Dias Taetz, Bertram Stifter, Thomas Stricker, Didier IEE SA Bissen Luxembourg Univ Kaiserslautern Kaiserslautern Germany German Res Ctr Artificial Intelligence Kaiserslautern Germany

ISBN: (纸本)9780738142661

images recorded during the lifetime of computer vision based systems undergo a wide range of illumination and environmental conditions affecting the reliability of previously trained machine learning models. image normalization is hence a valuable preprocessing component to enhance the models' robustness. To this end, we introduce a new strategy for the cost function formulation of encoder-decoder networks to average out all the unimportant information in the input images (e.g. environmental features and illumination changes) to focus on the reconstruction of the salient features (e.g. class instances). Our method exploits the availability of identical sceneries under different illumination and environmental conditions for which we formulate a partially impossible reconstruction target: the input image will not convey enough information to reconstruct the target in its entirety. Its applicability is assessed on three publicly available datasets. We combine the triplet loss as a regularizer in the latent space representation and a nearest neighbour search to improve the generalization to unseen illuminations and class instances. The importance of the aforementioned post-processing is highlighted on an automotive application. To this end, we release a synthetic dataset of sceneries from three different passenger compartments where each scenery is rendered under ten different illumination and environmental conditions: https://***

关键词： Computer vision Computational modeling Lighting Lightning machine learning Cost function Robustness

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Recognizing the Emotions Evoked by Artworks Through Visual Features and Knowledge Graph-Embeddings 1

引用

21st International Conference on image Analysis and processing (ICIAP)

作者： Aslan, Sinem Castellano, Giovanna Digeno, Vincenzo Migailo, Giuseppe Scaringi, Raffaele Vessio, Gennaro Ca Foscari Univ Venice Dept Environm Sci Informat & Stat Venice Italy Univ Bari Aldo Moro Dept Comp Sci Bari Italy

ISBN: (数字)9783031133213

ISBN: (纸本)9783031133213;9783031133206

Recognizing the emotion an image evokes in the observer has long attracted the interest of the community for its many potential applications. However, it is a challenging task mainly due to the inherent complexity and subjectivity of human feelings. Such a difficulty is exacerbated in the domain of visual arts, mainly because of their abstract nature. In this work, we propose a new version of the artistic knowledge graph we were working on, namely Artgraph, obtained by integrating the emotion labels provided by the ArtEmis dataset. The proposed graph enables emotion-based information retrieval and knowledge discovery even without training a learning model. In addition, we propose an artwork emotion classification system that jointly exploits visual features and knowledge graph-embeddings. Experimental evaluation revealed that while improvements in emotion classification depend mainly on the use of visual features, the prediction of style, genre and emotion can benefit from the simultaneous exploitation of visual and contextual features and can assist each other in a synergistic way.

关键词： Visual arts Digital humanities Computer vision Deep learning Knowledge graphs Emotion classification

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Computer vision for Supporting image Search

Computer Vision for Supporting Image Search

引用

7th International Conference on Advances in Visual Informatics, IVIC 2021

作者： Smeaton, Alan F. Insight Centre for Data Analytics Dublin City University 9 Glasnevin Dublin Ireland

ISBN: (纸本)9783030902346

Computer vision and multimedia information processing have made extreme progress within the last decade and many tasks can be done with a level of accuracy as if done by humans, or better. This is because we leverage the benefits of huge amounts of data available for training, we have enormous computer processing available and we have seen the evolution of machine learning as a suite of techniques to process data and deliver accurate vision-based systems. What kind of applications do we use this processing for? We use this in autonomous vehicle navigation or in security applications, searching CCTV for example, and in medical image analysis for healthcare diagnostics. One application which is not widespread is image or video search directly by users. In this paper we present the need for such image finding or re-finding by examining human memory and when it fails, thus motivating the need for a different approach to image search which is outlined, along with the requirements of computer vision to support it. © 2021, Springer Nature Switzerland AG.

关键词： Computer vision

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