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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

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No-regret online learning over riemannian manifolds 21

No-regret online learning over riemannian manifolds

引用

Proceedings of the 35th International conference on Neural Information processing systems

作者： xi Wang Zhipeng Tu Yiguang Hong Yingyi Wu Guodong Shi AMSS Chinese Academy of Sciences Beijing China Tongji University Shanghai China University of Chinese Academy of Sciences Beijing China The University of Sydney NSW Australia

ISBN: (纸本)9781713845393

We consider online optimization over Riemannian manifolds, where a learner attempts to minimize a sequence of time-varying loss functions defined on Riemannian manifolds. Though many Euclidean online convex optimization algorithms have been proven useful in a wide range of areas, less attention has been paid to their Riemannian counterparts. In this paper, we study Riemannian online gradient descent (R-OGD) on Hadamard manifolds for both geodesically convex and strongly geodesically convex loss functions, and Riemannian bandit algorithm (R-BAN) on Hadamard homogeneous manifolds for geodesically convex functions. We establish upper bounds on the regrets of the problem with respect to time horizon, manifold curvature, and manifold dimension. We also find a universal lower bound for the achievable regret by constructing an online convex optimization problem on Hadamard manifolds. All the obtained regret bounds match the corresponding results are provided in Euclidean spaces. Finally, some numerical experiments validate our theoretical results.

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Performance and Comparison Analysis of image processing Based Forest Fire Detection 4th

Performance and Comparison Analysis of Image Processing Base...

引用

4th International conference on Nanoelectronics, Circuits and Communication systems, NCCS 2018

作者： Singh, Lucky Kumar, Ashok Priyadarshi, Rahul Department of Electronics and Communication Engineering National Institute of Technology HamirpurHP177005 India Department of Electronics and Communication Engineering National Institute of Technology PatnaBihar800005 India

ISBN: (纸本)9789811528538

A wildland fire is an unrestrained fire that happens mostly in forest regions, though it can additionally occupy agricultural or urban regions. Some of the foremost reasons of wildfires: human elements, both premeditated and unintended, are the most typical ones. The quantity and effect of forest fires are anticipated to rise due to the global warming. So as to combat against those catastrophes, it is vital to espouse an inclusive, convoluted approach that allows a continuous situational cognizance and immediate awareness. This paper describes the analysis of existing forest fire detection method and further simulations of all existing method have been done using MATLAB Tool. It has been also noticed that if the optimal algorithms can be implemented for each and every part of detecting motion zone and take out the fire characteristics, the performance of system may be further enhanced. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Fires

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Multimedia Forensics - An approach to detect and analyze Human faces in multimedia files 5

Multimedia Forensics - An approach to detect and analyze Hum...

引用

5th International conference on image Information processing (ICIIP)

作者： Gowada, Raghavendra Pawar, Digambar Tetali, Satish Reddy Univ Hyderabad Sch CIS Hyderabad Telangana India

ISBN: (纸本)9781728108995

Manual Security is being replaced by video surveillance systems by the advent of multimedia forensics. Face detection is an important technique in multimedia forensics. Many proposed methods identify and localize the faces in an image or in an image sequence. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Since, innumerable video data that is collected from video surveillance are to be automatically processed and get valuable information out of it, we need to scale the processing framework accordingly. In this paper, we propose face recognition system and minimize the overall processing time of large data set using parallel processing method. Given a video from a video surveillance, we need to convert it to frames, detect the human faces in these frames and recognize the face by comparing with a given face or comparing against database entries where criminal data is present. We use cascade classifier that takes a vector of features (decision variables) and results the probability that the vector belongs to the class. Using cascade classifier, we identify the faces from a given image and finally compare the faces with database entries.

关键词： Video surveillance Multimedia forensics Face detection Face recognition Parallel processing Cascade classifier Decision variables Spark streaming YARN Mapreduce

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The Comparison of Color Texture Features Extraction based on 1D GLCM with Deep Learning Methods

The Comparison of Color Texture Features Extraction based on...

引用

International conference on systems, Signals and image processing, IWSSIP

作者： Miroslav Benco Patrik Kamencay Martina Radilova Robert Hudec Martin Sinko University of Zilina Zilina Slovakia

ISBN: (数字)9781728175393

ISBN: (纸本)9781728175409

In this paper, the comparison between deep learning methods and feature extraction algorithms is presented. The principle of Grey-Level Co-occurrence Matrix (GLCM) and its modifications are used for our research. The main idea was to design a method for the description of combined features and textures. The texture classification process is carried out with the robust support vector machine classifier (SVM). We compare these feature extraction methods with proposed Convolutional Neural Networks (CNN). This proposed network contains 25 layers. Finally, the all evaluation and comparison of color texture retrieval results for all used methods are presented. The all feature extraction algorithms and proposed CNN have been tested on two different color texture datasets (Outex and Vistex datasets).

关键词： image color analysis Feature extraction image retrieval Support vector machines Machine learning Classification algorithms

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CONTINUAL PALMPRINT RECOGNITION WITHOUT FORGETTING 26

CONTINUAL PALMPRINT RECOGNITION WITHOUT FORGETTING

引用

26th IEEE International conference on image processing (ICIP)

作者： Du, Xuefeng Zhong, Dexing Shao, Huikai Xi An Jiao Tong Univ Sch Elect & Informat Engn 28 West Xianning Rd Xian 710049 Shaanxi Peoples R China

ISBN: (纸本)9781538662496

As a promising topic of biometrics, palmprint recognition helps to effectively verify a person's identity, which is suitable for building a security system. Recent progress has achieved high recognition accuracy in different benchmark datasets due to deep learning. However, these applications are almost implemented in one dataset with iterative training epochs to help neural network generalize. When applied practically where many new users' palmprints registered in sequence, deep learning-based recognition systems cannot avoid the problem of catastrophic forgetting. In this paper, we propose a continual learning framework based on reinforcement learning to dynamically expand the neural network when facing newly registered palmprints without costly retraining or fine-tuning. Experiments on different datasets demonstrate the high adaptability of our model that is promising for solving the forgetting attack of every biometric system.

关键词： Biometrics Palmprint recognition Continual learning Information security

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Algorithm for Fog-degraded image Enhancement Based on Adaptive Fractional-order PDE

Algorithm for Fog-degraded Image Enhancement Based on Adapti...

引用

IEEE International conference on Signal and image processing (ICSIP)

作者： Ran Zhang Fengqun Zhao Fang Dai Yatao Shi School of Sciences Xi’an University of Technology Xi’an ShaanXi China

ISBN: (数字)9781728168968

ISBN: (纸本)9781728168975

In this study, an image enhancement model based on an inverse diffusion equation with a Riesz fractional derivative is developed. The optimal orders of fractional derivatives for the images are obtained through experiments, and six quantities associated with the brightness and texture of each haze image-mean, variance, skewness, kurtosis, two-norm, and contrast-are calculated. By regression analysis, the linear relationship between the optimal order of the fractional derivative and these statistical quantities is acquired. Finally, the empirical formula for the order of the fractional derivative for the differential equation model is obtained. Experimental results show that the adaptive order of the fractional differential obtained using our approach is close to the optimal order obtained using artificial experiments and that the enhancement effect is optimal. Compared with other image enhancement algorithms, our algorithm can better improve the brightness and contrast of images and provide a better visual effect while defogging. Two objective evaluation indexes- information entropy and average gradient-also indicate the effectiveness of our method.

关键词： Adaptation models Atmospheric modeling Brightness Differential equations Mathematical model Information entropy image enhancement

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A Motion Blurred image Restoration Algorithm Based on CycleGAN 14

A Motion Blurred Image Restoration Algorithm Based on CycleG...

引用

14th IEEE International conference on Intelligent systems and Knowledge Engineering, ISKE 2019

作者： Wu, Chen Chen, LiJun Li, Dan Xian University of Posts Telecommunications Department of Computer Xi'an China Xi' an University of Technology Department of Computer Science and Engineering Xi'an China

ISBN: (纸本)9781728123486

An end-to-end blurred image restoration algorithm based on CycleGAN is proposed to solve the complicated problems of obtaining real paired data sets of moving blurred images and simulating real blurred images with manually generated blurred images. In CycleGAN, only using the loss of average absolute error (L1) as the reconstruction loss wm lead to the problems of artifact, color distortion and unclear image in the restored image. The problem of image artifact and unclear image can be solved by introducing the loss of structural similarity measure (SSIM) and the color distortion can be solved by the loss of color saturation. The experimental results show that compared with several deblurring algorithms with better restoration results, the restoration results produced by the algorithm in this paper are significantly improved in qualitative and quantitative evaluation. © 2019 IEEE.

关键词： image reconstruction

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Fault Diagnosis of Power Equipment Based on Infrared image Analysis

Fault Diagnosis of Power Equipment Based on Infrared Image A...

引用

Advances in Electrical Engineering and Computer Applications( AEECA), 2020 IEEE International conference on

作者： Chenxi Guo Ming Ren Changjie xia Ming Dong Bin Wang State Key Laboratory of Electrical Insulation for Power Equipment Xi’an Jiaotong University Xi’an China

ISBN: (数字)9781728165219

ISBN: (纸本)9781728165226

As the need to discover abnormal temperature rise and overheating breakdown of power equipment in substations is urgent, infrared inspection is important for its quick and accurate characteristics. To improve the accuracy of infrared inspection diagnosis, this paper proposes an operational diagnosis system based on comprehensive analysis of infrared images of power equipment. Firstly, the image is preprocessed by histogram equalization, Sobel operator, Canny operator, median filtering, etc. Then, the feature points of the infrared image are extracted by SIFT algorithm, and the extracted feature points are K-means clustered. Find the type of feature points that belong to the capacitive device after clustering, and then perform SIFT feature extraction on the processed image, and eliminate the feature points that are not electrical devices according to the found feature points, thereby completing the target -- Identification of the electrical device. Finally, the target recognition results of the 3 pretreatment methods and the original without pretreatment are compared to find the best effect, that is, the pre-processing algorithm with the highest recognition accuracy.

关键词： Feature extraction Filtering Histograms image edge detection Clustering algorithms Target recognition Filtering algorithms

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Task-driven image Preprocessing Algorithm Evaluation Strategy

Task-driven Image Preprocessing Algorithm Evaluation Strateg...

引用

International conference on Dependable systems and Their Applications (DSA)

作者： PengQi Wang Lin Geng DongBo Zhao ShuTing Kang Qian Dong Guang Yang Yuan Shi LingZhong Meng YunZhi Xue Institute of Software Chinese Academy of Sciences Beijing China Beijing Institute of System Engineering Beijing China

ISBN: (数字)9780738124223

ISBN: (纸本)9781665419536

The image preprocessing algorithm can effectively improve performance of the advanced visual algorithms under complex conditions. But the evaluation of the image preprocessing algorithm usually uses the traditional PSNR/SSIM indicators, there is a big gap between the evaluation result and the performance of the algorithm in actual vision tasks. This article uses the UE4 virtual engine and referring to the atmospheric scattering model to construct a haze vehicle small object dataset (VSOD). Based on virtual data, a vision task-driven image preprocessing algorithm evaluation strategy is proposed. We take dehazing algorithms and object detection tasks as examples to verify the task-driven evaluation strategy. By analyzing the evaluation results of task-driven evaluation strategy and traditional PSNR/SSIM, we proved that the task-driven evaluation strategy can more accurately evaluate the performance of image preprocessing algorithms in actual vision tasks.

关键词： Visualization Atmospheric modeling Scattering Object detection Task analysis Engines

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Shift, rotation and scale invariant optical fingerprint verification system with double random phase encoding

Shift, rotation and scale invariant optical fingerprint veri...

引用

3rd Asian conference on Artificial Intelligence Technology, ACAIT 2019

作者： Zhuo, Shengkai Jiao, Shuming Zou, Wenbin Wang, Na Li, xia Guangdong Provincial Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen University Shenzhen China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen China Nanophotonics Research Centre College of Optoelectronic Engineering Shenzhen University Shenzhen China

Biometric features such as fingerprint images can be authenticated by not only computer algorithms but also optical systems. In previous works, double random phase encoding (DRPE) optical lens system is employed for fingerprint verification. However, such a system can yield authentication failure when the key is generated from a slightly distorted fingerprint image. In this work, a fingerprint image pre-processing scheme for DRPE fingerprint optical authentication system is proposed. Simulated experimental results demonstrate the proposed method has significantly better robustness to shift, rotation and scale variance than some of the conventional DRPE-based approaches. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Authentication

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