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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

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Real-time heat sealing quality analysis of film based on digital twin system 3

Real-time heat sealing quality analysis of film based on dig...

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3rd international conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Zhao, Jun Shen, Nanyan Li, Jing Li, Yufei Li, Haoyang School of Mechatronic Engineering and Automation Shanghai University Shanghai Baoshan China

ISBN: (纸本)9781510680449

Digital twin achieves interactive mapping between physical entities and virtual models, enabling continuous real-time monitoring of process quality in virtual spaces. This paper addresses the issues of high latency and poor correlation with heat sealing process parameters in the quality inspection of plastic film heat sealing, and explores real-time analysis of heat sealing quality based on digital twin technology. The focus is on the finite element analysis of typical heat sealing process parameters combined with thermo-structural coupling, boundary condition modification and data-driven modeling. The study reveals the relationship between controllable heat sealing process parameters and film heat sealing quality, achieving real-time monitoring of the heat sealing quality of plastic sealing film © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Quality control

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Research on Global Illumination Exploration in Dynamic Scenes 3

Research on Global Illumination Exploration in Dynamic Scene...

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3rd international conference on computer vision and Pattern Analysis, ICCPA 2023

作者： Ji, Xiu Yang, Huamin Han, Cheng School of Computer Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China School of Electrical and Information Engineering Changchun Institute of Technology Jilin Changchun130012 China

ISBN: (纸本)9781510667563

Neural rendering can achieve satisfactory illumination effects with unknown light source locations and brightness. When training on dynamic scenarios (where object positions, textures, lighting, and viewpoints can vary), variations in object position, material properties, light intensity, and angle make the training results unsatisfactory due to the influence of global light sources. This paper proposes a novel global illumination exploration method, which uses Markov Chain Monte Carlo (MCMC) to perform small sample sampling of light points, and incorporates a new Bayesian optimization (Randomized Search) strategy to optimize the sample data combined with real-time data to remove sampling redundant information and improve training efficiency. The comprehensive experimental results show that our proposed method provides a practical and effective solution for the study of global illumination in dynamic scenes. © 2023 SPIE.

关键词： Light sources

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Non-ellipsoidal Extended Object Tracking using PMBM filter 3

Non-ellipsoidal Extended Object Tracking using PMBM filter

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3rd international conference on computer vision and Pattern Analysis, ICCPA 2023

作者： Zhang, Youan Li, Peng Zhang, Wenjie Wang, Jie Zhang, Kejie School of Computer Engineering Jiangsu University of Technology Changzhou213001 China

ISBN: (纸本)9781510667563

The Poisson multi-Bernoulli mixture (PMBM) filter is an effective tracking framework for tracking multiple extended objects. However, methods based on this framework typically assume that the object's shape is an ellipse, which cannot adequately describe the object's shape. When two objects are spatially close, problems such as difficulty correctly distinguishing the object trajectory and insufficient utilization of the object shape's feature information arise. To address the aforementioned issues, this paper describes the shape of the object in greater detail using the multi-ellipse model. On this premise, the extended object shape will be divided into multiple Gaussian inverse Wishart components, and the likelihood will be calculated. Furthermore, a new partitioning method is proposed to divide the measurements into several most linearly dependent components, which aids in estimating the object shape composed of multiple ellipses. The simulation results show that the new algorithm outperforms the original PMBM algorithm in terms of accuracy. © 2023 SPIE.

关键词： Inverse problems

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A UAV Detection Framework Based on Dual Stereo vision System for Low-Altitude Urban Background 3

A UAV Detection Framework Based on Dual Stereo Vision System...

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3rd international conference on computer vision and Pattern Analysis, ICCPA 2023

作者： Zhu, Renwei Chen, Jun Yang, Zhao Li, Na School of Transportation Southeast University Nanjing China College of General Aviation and Flight Nanjing University of Aeronautics and Astronautics Nanjing China College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9781510667563

This paper establishes a dual stereo vision system and uses Zhang's calibration method to calculate the homography matrix and various parameters of the binocular camera to achieve system correction. The effect of different processing methods on the UAV image in a low-altitude urban background is analyzed. A multistage filter fusion algorithm combined with various filtering and segmentation methods is designed to realize the background suppression of the low-altitude urban background UAV image and drone target extraction. An improved image processing method is used to suppress the background of a single frame image of a video sequence. The image information other than the UAV is regarded as noise or background. The noise and background are subtracted to finally get the UAV image. This research provides a framework for UAV detection in low-altitude airspace, which can support urban airspace management. © 2023 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Algorithmization of the process of managing commercial projects, taking into account the formalization of the company s financing process 3

Algorithmization of the process of managing commercial proje...

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3rd international conference on Optics, computer Applications, and Materials Science, CMSD 2023

作者： Khorev, A.I. Lapshina, M.L. Lukina, O.O. Lapshin, D.D. Kolomytseva, O. Yu. Voronezh State University of Engineering Technologies Voronezh Russia Voronezh State Forestry Engineering University Named after G.F. Morozov Voronezh Russia Budgetary Educational Institution Novousmansky Educational Center Novaya Usman Village Voronezh region Russia

ISBN: (纸本)9781510674486

The work defines the features of financing the company's commercial projects, taking into account the formulated additional functions of financing based on the possible variability of al-Ternatives for the long-Term management of the company. The possibility of using a decomposi-Tion approach when choosing a solution to a global problem is substantiated, as well as an algo-rithm for generating a complete set of target indicators that satisfy specified restrictions at the lower hierarchical level. The possibility of using elements of the graph approach in the procedure for comparing budget options is substantiated, and statements are formulated that guarantee the reliability of preference relations for a specific criterion. © 2024 SPIE. All rights reserved.

关键词： Budget control

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AI-Driven Depression Detection Algorithms from Visual and Audio Cues 3

AI-Driven Depression Detection Algorithms from Visual and Au...

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3rd international conference on Frontiers of Electronics, Information and Computation Technologies, ICFEICT 2023

作者： Gu, Yating Zhang, Chi Ma, Fei Jia, Xiaojian Ni, Shiguang Tsinghua University Shenzhen International Graduate School Shenzhen China Huawei Cloud Shenzhen China Shenzhen Mental Health Center Shenzhen Kangning Hospital Shenzhen China

ISBN: (纸本)9798350302356

Depression is a widespread psychiatric disorder, however, its outpatient rate remains low in many countries. To address the limitations of current depression screening methods, this study develops computer-aided algorithms for detecting depressive symptoms using a standardized depression detection dataset collected from hospitals. This study analyzes visual and audio cues of depression patients and healthy controls. Facial behavior is evaluated with a combination of visual features, including facial landmarks, action units, and eye gaze direction extracted from video frames, while verbal expressions are analyzed through a set of distinct features, such as the Mel Spectral Cepstral Coefficient (MFCC), loudness, and fundamental frequency (F0). These features are utilized to train models including random forest (RF), convolutional neural network (CNN), and recurrent neural network (RNN). Further, this paper proposes an attention-based multimodal fusion network using BiLSTM for feature representations and multi-head attention for visual-audio feature fusion. This paper achieves an F1 score of 0.8761, 0.7943, and 0.9278 for visual, audio, and visual-audio modality, respectively. By extracting easily interpretable features based on the characteristics and markers of patients with depression and applying AI algorithms, this study demonstrates the potential of AI-driven depression detection methods. © 2023 IEEE.

关键词： computer vision

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ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis 1

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3rd Workshop on Deep Generative Models for Medical Image Computing and computer Assisted Intervention (DGM4MICCAI) at the 26th international conference on Medical Image Computing and computer Assisted Intervention (MICCAI)

作者： Xu, Xuan Kapse, Saarthak Gupta, Rajarsi Prasanna, Prateek SUNY Stony Brook New York NY 11794 USA

ISBN: (数字)9783031537677

ISBN: (纸本)9783031537660;9783031537677

Generative AI has received substantial attention in recent years due to its ability to synthesize data that closely resembles the original data source. While Generative Adversarial Networks (GANs) have provided innovative approaches for histopathological image analysis, they suffer from limitations such as mode collapse and overfitting in discriminator. Recently, Denoising Diffusion models have demonstrated promising results in computer vision. These models exhibit superior stability during training, better distribution coverage, and produce high-quality diverse images. Additionally, they display a high degree of resilience to noise and perturbations, making them well-suited for use in digital pathology, where images commonly contain artifacts and exhibit significant variations in staining. In this paper, we present a novel approach, namely ViT-DAE, which integrates vision transformers (ViT) and diffusion autoencoders for high-quality histopathology image synthesis. This marks the first time that ViT has been introduced to diffusion autoencoders in computational pathology, allowing the model to better capture the complex and intricate details of histopathology images. We demonstrate the effectiveness of ViT-DAE on three publicly available datasets. Our approach outperforms recent GAN-based and vanilla DAE methods in generating realistic images.

关键词： Keywords: Histopathology Diffusion Autoencoders vision Transformers

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Optimization of the process of 3D character design and production for 3D artists 24

Optimization of the process of 3D character design and produ...

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3rd international conference on computer, Artificial Intelligence and control Engineering, CAICE 2024

作者： Zeng, Weijia Software Engineering Institute of Guangzhou Guangzhou China

ISBN: (纸本)9798400716942

This article mainly discusses the optimization of the process of 3D character design and production for 3D artists. We address the problems faced in the current 3D character design and production process, emphasizing the concept of art first, allowing artists to more freely express their creativity in the design and production process. We propose a nonlinear process and method based on digital sculpting technology, supported by dynamic mesh, topological reconstruction, projecting and polypainting, texture baking, etc, to improve design efficiency and artistic expression. © 2024 ACM.

关键词： 3D modeling

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Highway Traffic Flow control Model and Simulation Based on Fuzzy control 3

Highway Traffic Flow Control Model and Simulation Based on F...

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3rd international conference on computer Science, Electronic Information Engineering and Intelligent control Technology, CEI 2023

作者： Nie, Binghua Ma, Bin Henan Ruisheng Intelligent Technology Co. Ltd Zhengzhou China School of Information Engineering North China University of Water Resources and Hydropower Zhengzhou China

ISBN: (纸本)9798350372052

With the continuous expansion of the scale of highways, the growing contradiction between traffic demand and capacity has become an undeniable societal issue. Preventing congestion on highways and improving the efficiency of road usage has always been a focal point of research in the field of highway traffic control. In order to enhance the traffic operating environment, this paper establishes a traffic flow control simulation model and designs a fuzzy control algorithm to simulate the traffic flow state on highways. Subsequently, a comparative analysis is conducted on the traffic states under different strategies, including no-control, ALINEA control, and fuzzy control. To further demonstrate the effectiveness of fuzzy control, this paper relies on real data from the Xibao Expressway to simulate the traffic flow under fuzzy control. The results indicate that under equivalent conditions, the fuzzy control method can achieve superior performance. © 2023 IEEE.

关键词： Fuzzy control

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MUWS 2024: The 3rd international Workshop on Multimodal Human Understanding for the Web and Social Media 24

MUWS 2024: The 3rd International Workshop on Multimodal Huma...

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4th Annual international conference on Multimedia Retrieval (ICMR)

作者： Kastner, Marc A. Cheema, Gullal S. Hakimov, Sherzod Garcia, Noa Kyoto Univ Kyoto Japan Leibniz Univ Hannover L3S Res Ctr Hannover Germany Univ Potsdam Potsdam Germany Osaka Univ Osaka Japan

ISBN: (纸本)9798400706028

Multimodal human understanding and analysis are emerging research areas that cut through several disciplines like computer vision (CV), Natural Language Processing (NLP), Speech Processing, Human-computer Interaction (HCI), and Multimedia. Several multimodal learning techniques have recently shown the benefit of combining multiple modalities in image-text, audio-visual and video representation learning and various downstream multimodal tasks. At the core, these methods focus on modelling the modalities and their complex interactions by using large amounts of data, different loss functions and deep neural network architectures. However, for many Web and Social media applications, there is the need to model the human, including the understanding of human behaviour and perception. For this, it becomes important to consider interdisciplinary approaches, including social sciences and psychology. The core is understanding various cross-modal relations, quantifying bias such as social biases, and the applicability of models to real-world problems. Interdisciplinary theories such as semiotics or gestalt psychology can provide additional insights on perceptual understanding through signs and symbols across multiple modalities. In general, these theories provide a compelling view of multimodality and perception that can further expand computational research and multimedia applications on the Web and Social media. The theme of the MUWS workshop, multimodal human understanding, includes various interdisciplinary challenges related to social bias analyses, multimodal representation learning, detection of human impressions or sentiment, hate speech, sarcasm in multimodal data, multimodal rhetoric and semantics, and related topics. The MUWS workshop is an interactive event and includes keynotes by relevant experts, a poster session, research presentations and discussion.

关键词： multimodality machine learning image-text relations social media web human understanding semiotics

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