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检索条件"任意字段=16th International Conference on Computer Graphics and Vision, GraphiCon 2006"

共 230 条记录，以下是41-50 订阅

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AI-assisted Automated Pipeline for Length Estimation, Visual Assessment of the Digestive Tract and Counting of Shrimp in Aquaculture Production 16

AI-assisted Automated Pipeline for Length Estimation, Visual...

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16th international Joint conference on computer vision, Imaging and computer graphics theory and Applications (VISIGRAPP) / 16th international conference on computer vision theory and Applications (VISAPP)

作者： Hashisho, Yousif Dolereit, Tim Segelken-Voigt, Alexandra Bochert, Ralf Vahl, Matthias Fraunhofer Inst Comp Graph Res IGD Joachim Jungius Str 11 D-18059 Rostock Germany State Res Ctr Agr & Fisheries Mecklenburg Vorpomm Inst Fisheries Sudstr 8 D-18375 Born Germany

ISBN: (纸本)9789897584886

Shrimp farming is a century-old practice in aquaculture production. In the past years, some improvements of the traditional farming methods have been made, however, it still involves mostly intensive manual work, which makes traditional farming a neither time nor cost efficient production process. therefore, a continuous monitoring approach is required for increasing the efficiency of shrimp farming. this paper proposes a pipeline for automated shrimp monitoring using deep learning and image processing methods. the automated monitoring includes length estimation, assessment of the shrimp's digestive tract and counting. Furthermore, a mobile system is designed for monitoring shrimp in various breeding tanks. this study shows promising results and unfolds the potential of artificial intelligence in automating shrimp monitoring.

关键词： computer vision Image Processing AI Deep Learning Shrimp Aquaculture

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SYMBOLIC MODEL CHECKING FOR MODULAR SYSTEMS 16

SYMBOLIC MODEL CHECKING FOR MODULAR SYSTEMS

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16th international conference on computer graphics, Visualization, computer vision and Image Processing, CGVCVIP 2022, 8th international conference on Connected Smart Cities, CSC 2022, 7th international conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2022, and 11th international conference on theory and Practice in Modern Computing, TPMC 2022 - Held at the 16th Multi conference on computer Science and Information Systems, MCCSIS 2022

作者： Ouazar, F. Boukala, M.C. Ioualalen, M. MOVEP Computer Science Department USTHB BP 32 El-Alia Algiers Algeria

ISBN: (纸本)9789898704429

Model checking verification is a formal and fully automatic method widely used for checking critical and complex systems. It is based on reachability analysis, which often encounters the state space explosion problem. In this paper, we present our approach to mitigate this problem;we propose to use a hybrid solution based on symbolic representation of a system in a modular way. We proposed a symbolic method for CTL\X properties check on modular systems. © MCCSIS *** rights reserved.

关键词： Model checking

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Towards Real-time Object Recognition and Pose Estimation in Point Clouds 16

Towards Real-time Object Recognition and Pose Estimation in ...

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作者： Marcon, Marlon Pereira Bellon, Olga Regina Silva, Luciano Univ Tecnol Fed Parana Dapartment Software Engn Dois Vizinhos Brazil Univ Fed Parana Dept Comp Sci Curitiba Parana Brazil

ISBN: (纸本)9789897584886

Object recognition and 6DoF pose estimation are quite challenging tasks in computer vision applications. Despite efficiency in such tasks, standard methods deliver far from real-time processing rates. this paper presents a novel pipeline to estimate a fine 6DoF pose of objects, applied to realistic scenarios in real-time. We split our proposal into three main parts. Firstly, a Color feature classification leverages the use of pre-trained CNN color features trained on the ImageNet for object detection. A Feature-based registration module conducts a coarse pose estimation, and finally, a Fine-adjustment step performs an ICP-based dense registration. Our proposal achieves, in the best case, an accuracy performance of almost 83% on the RGB-D Scenes dataset. Regarding processing time, the object detection task is done at a frame processing rate up to 90 FPS, and the pose estimation at almost 14 FPS in a full execution strategy. We discuss that due to the proposal's modularity, we could let the full execution occurs only when necessary and perform a scheduled execution that unlocks real-time processing, even for multitask situations.

关键词： Transfer Learning 3D computer vision Feature-based Registration ICP Dense Registration RGB-D Images

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Implementing OpenVX on a Polymorphous Array Processor 16

Implementing OpenVX on a Polymorphous Array Processor

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IEEE 16th international conference on Communication Technology (ICCT)

作者： Guo, Zhiquan Han, Jungang Li, Tao Xian Univ Posts & Telecommun Xian Peoples R China

ISBN: (纸本)9781467370059

this paper presents an implementation of OpenVX on the PAAG array processor (Polymorphic Array Architecture for graphics and image processing), which is a novel poly morphous architecture designed for graphics rendering and image processing. Open VX is a new standard for imp lementing and optimizing low-level image processing and computer vision released by Khronos. It uses a graph-based execution model to combine function enabling both task and data-independent execution. We propose two Open VX graph mapping modes for PAAG: Whole Graph Mapping (WGM) and Single Node Mapping (SNM). Experimental results indicate that the two modes are both effective, but WGM is better that SNM in terms of efficiency, the experiments also illustrates PAAG has a great potential on image processing and computer vision on array processor.

关键词： OpenVX OpenVX graph mapping Image processing computer vision

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Poster: Virtual scene as a software component

Poster: Virtual scene as a software component

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16th international conference in Central Europe on computer graphics, Visualization and computer vision 2008, WSCG'2008

作者： Ošlejšek, Radek Masaryk University Botanicka 68a 602 00 Brno Czech Republic

ISBN: (纸本)9788086943152

graphics systems use many advanced techniques that enable to model and visualize a virtual scene with varying level of realism. Unfortunately, rendering algorithms significantly differ in the way how they process a virtual scene. Concrete implementations therefore usually lead to monolithic solutions. In this paper we propose the concept of a component-based scene graph, i.e. an independent scene graph, which can be used by many rendering strategies simultaneously and, moreover, which can be easily replaced with another implementation.

关键词： Rendering (computer graphics)

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Video Action Classification through Graph Convolutional Networks 16

Video Action Classification through Graph Convolutional Netw...

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作者： Costa, Felipe F. Saito, Priscila T. M. Bugatti, Pedro H. Univ Tecnol Fed Parana Dept Comp 1640 Alberto Carazzai Ave Cornelio Procopio Brazil

ISBN: (纸本)9789897584886

Video classification methods have been evolving through proposals based on end-to-end deep learning architectures. Several works have testified that end-to-end models are effective for the learning of intrinsic video features, especially when compared to the handcrafted ones. In general, convolutional neural networks are used for deep learning in videos. Usually, when applied to such contexts, these vanilla deep learning networks cannot identify variations based on temporal information. To do so, memory-based cells (e.g. long-short term memory), or even optical flow techniques are used in conjunction with the convolutional process. However, despite their effectiveness, those methods neglect global analysis, processing only a small quantity of frames in each batch during the learning and inference process. Moreover, they also completely ignore the semantic relationship between different videos that belong to the same context. thus, the present work aims to fill these gaps by using information grouping concepts and contextual detection through graph-based convolutional neural networks. the experiments show that our method achieves up to 87% of accuracy in a well-known public video dataset.

关键词： Deep Learning Graph Convolutional Network computer vision Action Classification

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DESIGN CHALLENGES FOR AN ENERGY EXCHANGE PLATFORM ENABLING A SUCCESSFUL ENERGY TRANSITION 16

DESIGN CHALLENGES FOR AN ENERGY EXCHANGE PLATFORM ENABLING A...

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作者： Khanam, Zeba Bourazeri, Aikaterini University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom

ISBN: (纸本)9789898704429

Improving energy efficiency and reducing CO2 emissions are key strategic objectives for governments on an international level. Energy transition initiatives have been put in place to promote such measures and enhance decarbonisation efforts that can mitigate adverse climate change effects. Given that the energy transition equally focuses on the demand-side and is predicated on active consumer participation, we propose a new user infrastructure interface in which information visualisation and interface cues for energy consumption and efficiency are integrated within an Energy Exchange Platform. Following an innovate co-design methodology including a user survey for initial requirements, co-design workshops with end-users and usability testing, we aim to promote active consumer participation and other aspects of user engagement with critical infrastructure through information visualisation and interface cues. © MCCSIS *** rights reserved.

关键词： Energy efficiency

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Photo-Realistic Simulation of Road Scene for Data-Driven Methods in Bad Weather 16

Photo-Realistic Simulation of Road Scene for Data-Driven Met...

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16th IEEE international conference on computer vision (ICCV)

作者： Li, Kunming Li, Yu You, Shaodi Barnes, Nick CSIRO Data61 Canberra ACT Australia Australian Natl Univ Canberra ACT Australia Adv Digital Sci Ctr Singapore Singapore

ISBN: (纸本)9781538610343

Modern data-driven computer vision algorithms require a large volume, varied data for validation or evaluation. We utilize computer graphics techniques to generate a large volume foggy image dataset of road scenes with different levels of fog. We compare with other popular synthesized datasets, including data collected both from the virtual world and the real world. In addition, we benchmark recent popular dehazing methods and evaluate their performance on different datasets, which provides us an objectively comparison of their limitations and strengths. To our knowledge, this is the first foggy and hazy dataset with large volume data which can be helpful for computer vision research in the autonomous driving.

关键词： computer vision Meteorology Roads Computational modeling Autonomous vehicles Rendering (computer graphics) Image color analysis

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DOMAIN ADAPTATION IN IMAGE DEHAZING: EXPLORING thE USAGE OF IMAGES FROM VIRTUAL SCENARIOS 16

DOMAIN ADAPTATION IN IMAGE DEHAZING: EXPLORING THE USAGE OF ...

引用

作者： Sappa, Angel D. Suárez, Patricia L. Velesaca, Henry O. Carpio, Darío Escuela Superior Politécnica del Litoral ESPOL Campus Gustavo Galindo Km. 30.5 P.O. Box 09 Vía Perimetral 01-5863 Ecuador Computer Vision Center Campus UAB Bellaterra Barcelona08193 Spain

ISBN: (纸本)9789898704429

this work presents a novel domain adaptation strategy for deep learning-based approaches to solve the image haze removal problem. Firstly, a large set of synthetic images is generated by using a realistic 3D graphic simulator;these synthetic images contain different densities of haze, which are used for training the model that is later adapted to any real scenario. the adaptation process requires just a few images to fine-tune the model parameters. the proposed strategy allows overcoming the limitation of training a given model with few images. In other words, the proposed strategy implements the adaptation of a haze removal model trained with synthetic images to real scenarios. It should be noticed that it is quite difficult, if not impossible, to have large sets of pairs of real-world images (with and without haze) to train in a supervised way haze removal algorithms. Experimental results are provided showing the validity of the proposed domain adaptation strategy. © MCCSIS *** rights reserved.

关键词： Deep learning

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作者： Khattar, Joseph Hahn, Eike Telawi, Samer Schwarz, Michael Boercsoek, Josef ICAS Institute for Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (纸本)9789898704429

Recent advancements in the embedded systems field have resulted in more complicated systems with application-specific blocks (IP cores), often known as System on Chip (SoC) devices. Several redundancy-based embedded designs provide reliability and safety for SoC in aeronautics, automotive, industrial automation, railway, and space. In this paper, a Safety System-on-Chip heterogenous1oo2 architecture is presented. the design is based on two open-source and proven in-use cores, LEON3 from Cobham Gaisler and RISCV processors SweRV EH1 from Western Digital. the SoC is implemented on a Xilinx FPGA system and supplemented with conventional peripherals from the Xilinx IP library and Cobham Gaisler. A software comparator is included for a diagnostic. Each core has independent IPs, and the software comparator evaluates data from both cores;in case of deviation, the system is rendered to an energized safe state. © MCCSIS *** rights reserved.

关键词： System-on-chip

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