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Evolutionary Optimization of Neural Networks for Fire recognition

Evolutionary Optimization of Neural Networks for Fire Recogn...

引用

International conference on computer Engineering and Systems

作者： Magy Kandil Samir Shahin Amir Atiya Magda Fayek Atomic Energy Anthority Egypt Faculty of Engineering Cairo university Egypt

ISBN: (纸本)1424402719;1424402727

In this paper, the new hybrid algorithm is used as real time fire recognition algorithm in visual image sequences. For the purposes of real time fire pattern recognition tasks neural networks (NNs) are typically trained with respect of error function minimization by propagating a linear sum of errors. Recent studies in the fire vision recognition have confronted the problem of the inconstant and different shapes of fire which required improving generalization of the NNs. Experimental evidence is presented in this study demonstrating the general application potential of the framework by generating populations of ENN for recognition with a large number of fire shapes in different images, to show that our hybrid algorithm is capable of detecting real time fire vision by improving the generalization of NNs

关键词： Neural networks Fires Shape Image recognition Image sequences Evolutionary computation Stochastic processes Radiation detectors Power engineering and energy pattern recognition

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Accurate Tracking of Monotonically Advancing Fronts

Accurate Tracking of Monotonically Advancing Fronts

引用

conference on computer vision and pattern recognition (CVPR)

作者： M.S. Hassouna A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

A wide range of computer vision applications such as distance field computation, shape from shading, and shape representation require an accurate solution of a particular Hamilton-Jacobi (HJ) equation, known as the Eikonal equation. Although the fast marching method (FMM) is the most stable and consistent method among existing techniques for solving such equation, it suffers from large numerical error along diagonal directions as well as its computational complexity is not optimal. In this paper, we propose an improved version of the FMMthat is both highly accurate and computationally efficient for Cartesian domains. The new method is called the multi-stencils fast marching (MSFM), which computes the solution at each grid point by solving the Eikonal equation along several stencils and then picks the solution that satisfies the fast marching causality relationship. The stencils are centered at each grid point x and cover its entire nearest neighbors. In 2D space, 2 stencils cover the 8-neighbors of x, while in 3D space, 6 stencils cover its 26-neighbors. For those stencils that are not aligned with the natural coordinate system, the Eikonal equation is derived using directional derivatives and then solved using a higher order finite difference scheme.

关键词： computer vision Shape Finite difference methods Application software Computational complexity Nonlinear equations Partial differential equations Image processing Laboratories Grid computing

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Photo-Realistic Image Restoration in the Wild with Controlled vision-Language Models

Photo-Realistic Image Restoration in the Wild with Controlle...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Ziwei Luo Fredrik K. Gustafsson Zheng Zhao Jens Sjölund Thomas B. Schön Uppsala University Karolinska Institutet

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Though diffusion models have been successfully applied to various image restoration (IR) tasks, their performance is sensitive to the choice of training datasets. Typically, diffusion models trained in specific datasets fail to recover images that have out-of-distribution degradations. To address this problem, this work leverages a capable vision-language model and a synthetic degradation pipeline to learn image restoration in the wild (wild IR). More specifically, all low-quality images are simulated with a synthetic degradation pipeline that contains multiple common degradations such as blur, resize, noise, and JPEG compression. Then we introduce robust training for a degradation-aware CLIP model to extract enriched image content features to assist high-quality image restoration. Our base diffusion model is the image restoration SDE (IR-SDE). Built upon it, we further present a posterior sampling strategy for fast noise-free image generation. We evaluate our model on both synthetic and real-world degradation datasets. Moreover, experiments on the unified image restoration task illustrate that the proposed posterior sampling improves image generation quality for various degradations.

关键词： Degradation Training Image synthesis Pipelines Transform coding Diffusion models Feature extraction

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Monitoring Social Insect Activity with Minimal Human Supervision

Monitoring Social Insect Activity with Minimal Human Supervi...

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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Tarun Sharma Julian M. Wagner Sara Beery William B. Dickson Michael H. Dickinson Joseph Parker California Institute of Technology USA MIT USA

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Tracking the behavior of animals and their group dynamics in nature offers a crucial look into the delicate ecological networks that compose wildlife diversity. The velvety tree ant (Liometopum occidentale) is an ecologically dominant ant species found in South Western North America; their extensive foraging activity shapes forest communities, and their nests are a biodiversity hot-spot for a multitude of symbiotic invertebrates (myrmecophiles). Despite their vital role in the ecosystem, their activity is largely unstudied. In this work, we develop a multi-sensor camera trap, named ’Ethocam,’ to capture ant behavioral patterns in the field, and combine this technology with a computer vision approach to track colony activity in an undisturbed fashion. We demonstrate an accurate system for counting ants built with minimal human labeling. We show that L. occidentale activity drops rapidly through the morning and study the effect of environmental conditions on ant count. We also report the occurrences of the ants’ interactions with other invertebrates in our camera trap data. Together, these findings demonstrate the potential of our system to capture the behavior of Liometopum occidentale as well as its complex associations with various local species including symbionts, potentially at landscape scale. Our study provides proof of concept for the promise of low-cost remote monitoring of social insect populations.

关键词： Symbiosis computer vision Shape Insects Wildlife Vegetation Cameras

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An Accurate Segmentation-Based Scene Text Detector with Context Attention and Repulsive Text Border

An Accurate Segmentation-Based Scene Text Detector with Cont...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Xi Liu Gaojing Zhou Rui Zhang Xiaolin Wei Meituan-Dianping Group Beijing China

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193618

Scene text detection is one of the most challenging problems in computer vision and has attracted great interest. In general, scene text detection methods are divided into two categories: detection-based and segmentation-based methods. Recently, the segmentation-based methods are more and more popular due to their superior performances and the advantages of detecting arbitrary-shape texts. However, there still exist the following problems: (a) the misclassfication of the unexpected texts, (b) the split of long text lines, (c) the failure of separating very close text instances. In this paper, we propose an accurate segmentation-based detector, which is equipped with context attention and repulsive text border. The context attention incorporates global channel attention, non-local self-attention and spatial attention to better exploit the global and local context, which can greatly increase the discriminative ability for pixels. Due to the enhancement of pixel-level features, false positives and the misdetections of long texts are reduced. Besides, for the purpose of solving very close text instance, a repulsive pixel link, which focuses on the relationships between pixels at the border, is proposed. Experiments on several standard benchmarks, including MSRA-TD500, ICDAR2015, ICDAR2017-MLT and CTW1500, validate the superiority of the proposed method.

关键词： Convolution Decoding Feature extraction Detectors computer vision Benchmark testing Object detection

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Computational Science and Its Applications - ICCSA 2006 1

引用

丛书名： Lecture Notes in computer Science

1000年

作者： Marina Gavrilova Osvaldo Gervasi Vipin Kumar C. J. Kenneth Tan David Taniar Antonio Laganá Youngsong Mun Hyunseung Choo

ISBN: (数字)9783540340768

ISBN: (纸本)9783540340751

This ?ve-volume set was compiled following the 2006 International conference on Computational Science and its Applications, ICCSA 2006, held in Glasgow, UK, during May 8–11, 2006. It represents the outstanding collection of almost 664 refereed papers selected from over 2,450 submissions to ICCSA 2006. Computational science has ?rmly established itself as a vital part of many scienti?c investigations, a?ecting researchers and practitioners in areas ranging from applications such as aerospace and automotive, to emerging technologies such as bioinformatics and nanotechnologies, to core disciplines such as ma- ematics, physics, and chemistry. Due to the shear size of many challenges in computational science, the use of supercomputing, parallel processing, and - phisticated algorithms is inevitable and becomes a part of fundamental theore- cal research as well as endeavors in emerging ?elds. Together, these far-reaching scienti?c areas contributed to shaping this conference in the realms of state-- the-art computational science researchand applications, encompassing the fac- itating theoretical foundations and the innovative applications of such results in other areas.

关键词： Theory of Computation Software Engineering/Programming and Operating Systems Numeric Computing Information Systems and Communication Service Simulation and Modeling computer Imaging, vision, pattern recognition and Graphics

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Efficient Nonparametric Belief Propagation with Application to Articulated Body Tracking

Efficient Nonparametric Belief Propagation with Application ...

引用

conference on computer vision and pattern recognition (CVPR)

作者： T.X. Han Huazhong Ning T.S. Huang Beckman Institute and ECE Department University of Illinois Urbana-Champaign Urbana-Champaign IL USA

An efficient Nonparametric Belief Propagation (NBP) algorithm is developed in this paper. While the recently proposed nonparametric belief propagation algorithm has wide applications such as articulated tracking [22, 19], superresolution [6], stereo vision and sensor calibration [10], the hardcore of the algorithm requires repeatedly sampling from products of mixture of Gaussians, which makes the algorithm computationally very expensive. To avoid the slow sampling process, we applied mixture Gaussian density approximation by mode propagation and kernel fitting [2, 7]. The products of mixture of Gaussians are approximated accurately by just a few mode propagation and kernel fitting steps, while the sampling method (e.g. Gibbs sampler) needs many samples to achieve similar approximation results. The proposed algorithm is then applied to articulated body tracking for several scenarios. The experimental results show the robustness and the efficiency of the proposed algorithm. The proposed efficient NBP algorithm also has potentials in other applications mentioned above.

关键词： Belief propagation Sampling methods Inference algorithms Gaussian approximation Kernel Random variables computer vision Graphical models Robustness Gaussian processes

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Computational Science and Its Applications - ICCSA 2006 1

引用

丛书名： Lecture Notes in computer Science

1000年

作者： Marina Gavrilova Osvaldo Gervasi Vipin Kumar C. J. Kenneth Tan David Taniar Antonio Laganá Youngsong Mun Hyunseung Choo

ISBN: (数字)9783540340713

ISBN: (纸本)9783540340706

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Reconstruction in the Round Using Photometric Normals and Silhouettes.

Reconstruction in the Round Using Photometric Normals and Si...

引用

conference on computer vision and pattern recognition (CVPR)

作者： G. Vogiatzis C. Hernandez R. Cipolla Department of Engineering University of Cambridge Cambridge UK

This paper addresses the problem of obtaining complete, detailed reconstructions of shiny textureless objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under varying illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint and produces accurate reconstructions in full 3D. A number of images of the object are obtained from multiple viewpoints, under varying lighting conditions. Starting from the silhouettes, the algorithm recovers camera motion and constructs the object’s visual hull. This is then used to recover the illumination and initialise a multi-view photometric stereo scheme to obtain a closed surface reconstruction. The contributions of the paper are twofold: Firstly we describe a robust technique to estimate light directions and intensities and secondly, we introduce a novel formulation of photometric stereo which combines multiple viewpoints and hence allows closed surface reconstructions. The algorithm has been implemented as a practical model acquisition system. Here, a quantitative evaluation of the algorithm on synthetic data is presented together with a complete reconstruction of a challenging real object.

关键词： Photometry Image reconstruction Stereo vision Surface reconstruction Stereo image processing Shape Lighting Cameras computer vision Reflectivity

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Modulating Bottom-Up and Top-Down Visual Processing via Language-Conditional Filters

Modulating Bottom-Up and Top-Down Visual Processing via Lang...

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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Ilker Kesen Ozan Arkan Can Erkut Erdem Aykut Erdem Deniz Yü ret KUIS AI Center Ko&#x00E7 University Computer Engineering Department Ko&#x00E7 Amazon Search Computer Engineering Department Hacettepe University

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487405

How to best integrate linguistic and perceptual processing in multi-modal tasks that involve language and vision is an important open problem. In this work, we argue that the common practice of using language in a top-down manner, to direct visual attention over high-level visual features, may not be optimal. We hypothesize that the use of language to also condition the bottom-up processing from pixels to high-level features can provide benefits to the overall performance. To support our claim, we propose a U-Net-based model and perform experiments on two language-vision dense-prediction tasks: referring expression segmentation and language-guided image colorization. We compare results where either one or both of the top-down and bottom-up visual branches are conditioned on language. Our experiments reveal that using language to control the filters for bottom-up visual processing in addition to top-down attention leads to better results on both tasks and achieves competitive performance. Our linguistic analysis suggests that bottom-up conditioning improves segmentation of objects especially when input text refers to low-level visual concepts. Code is available at https://***/ilkerkesen/bvpr.

关键词： Visualization Image segmentation Image color analysis Grounding Computational modeling Process control Predictive models

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