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2011 International Conference on Information Science and Technology, ICIST 2011

作者： Bao, Gang Shen, Yi Zeng, Zhigang Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei 430074 China Key Laboratory of Image Processing and Intelligent Control Education Ministry of China Wuhan Hubei 430074 China

ISBN: (纸本)9781424494408

Memristor has received significant attentions since Strukov et al released their invention on April 30, 2008 at Nature Letters. Based on the model of Strukov et al, analytic expression of the internal state is obtained by applying voltage to the device. By using the constant in the expression of the internal state, memory property of the memristor is explained. © 2011 IEEE.

关键词： Memristors

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Replaying Styles for Continual Semantic Segmentation Across Domains 7th

Replaying Styles for Continual Semantic Segmentation Across...

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7th Asian Conference on Pattern Recognition, ACPR 2023

作者： Deng, Yao Xiang, Xiang Key Lab of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783031476365

In the context of Domain Incremental Learning for Semantic Segmentation, catastrophic forgetting is a significant issue when a model learns new geographical domains. While replay-based approaches have been commonly used to mitigate this problem by allowing the model to review past knowledge, they require additional storage space for old data, which may not be feasible in real-world applications. To address this limitation, we propose a style replay method that leverages the characteristics of low-level representations in CNN to require only one style feature for each domain, leading to a significant reduction in storage overhead. By fusing the style features of past domains with the semantic features of current data, our method enables style transfer for new domain data, thereby improving the model’s generalization ability to the domain. Through extensive experimental evaluations on various autonomous driving datasets, we demonstrate the efficacy of our proposed method in addressing the challenges of continual semantic segmentation under both label and domain shift, outperforming the previous state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Semantic Segmentation

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Optimal Ascent Guidance based on Direct Optimization Method

Optimal Ascent Guidance based on Direct Optimization Method

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2012 International Conference on Modelling,Identification and control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Xuefang Lu Yongji Wang Candidate of Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Hu Key Laboratory of Ministry of Educationfor Image Processing and Intelligent Control Huazhong Univers

ISBN: (纸本)9781467315241

In this paper, an optimal guidance algorithm is proposed for atmospheric *** optimal guidance algorithm updates the reference trajectory to deal with the impact of disturbance by solving an optimal control problem *** the strong nonlinear ascent dynamic, the optimal control problem is transformed into nonlinear programming problem by trajectory *** direct optimization method is implemented for this nonlinear programming *** a segment of the reference trajectory is updated by the optimal guidance *** to the small amount of the discrete nodes and the initial guess solution which is close to the optimization solution, the direct optimization method is fast enough to generate a new reference *** simulation for the Generic Hypersonic Vehicle model and scramjet engine is done for different cases of the aerodynamic coefficient *** results show the accuracy and the effectiveness of this optimal guidance algorithm.

关键词： Optimal Guidance, Ascent, Direct Optimization

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Handling multi-objective in an HTN planner for emergency decision-making

Handling multi-objective in an HTN planner for emergency dec...

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2013 IEEE Conference Anthology, ANTHOLOGY 2013

作者： Li, Minglei Wang, Hongwei Qi, Chao Liu, Dan Wang, Jian Wang, Zhe Systems Engineering Institute Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781479916603

There are many multi-objective planning problems in emergency decision-making domain. HTN planners were widely used in emergency decision-making, while they have limited ability to solve optimization, especially multi-objective optimization. Aimed to handling multi-objective in HTN planners, this paper proposes a novel method based on SHOP2, which is a domain-independent state-based forward HTN planner. The method uses a weighted vector to mirror the decision maker's performance for various objectives and an anytime search algorithm to improve the ability to find the best solution plan. Finally, a case of emergency evacuation is given to testify the effectiveness of the method. © 2013 IEEE.

关键词： Multiobjective optimization

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Fast KNN search for big data with set compression tree and best bin first 2

Fast KNN search for big data with set compression tree and b...

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2nd International Conference on Cloud Computing and Internet of Things, CCIOT 2016

作者： Chen, Zhenjie Yan, Jingqi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of Ministry of Education for System Control and Information Processing China Shanghai China

ISBN: (纸本)9781467398213

This paper proposes k nearest neighbors (kNN) search based on set compression tree (SCT) and best bin first (BBF) to deal with the problem for big data. The large compression rate by set compression tree is achieved by compressing the set of descriptors jointly instead of compressing on a per-descript or basis. So set compression tree has a good performance in kNN search at a low bit rate. At the same time, the best bin first (BBF) is a very efficient algorithm to find the approximately kNN from a large number of high dimensional feature descriptors. SCT-BBF is a novel exploration and it improves search performance in three aspects: First, SCT-BBF requires less memory footprint, which is important in big data age. Second, it increases accuracy compared traditional method like KD-Tree and original SCT. SCT-BBF can be used with other data processing methods like PCA and SIFT to perform better. Third, this paper adopts finer search to increase accuracy at a slight loss of speed. And it can extend to big data easily. © 2016 IEEE.

关键词： Big data

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Velocity-Varying Target Tracking of Mobile Sensor Network Based on Flocking control

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Journal of Shanghai Jiaotong university(Science) 2021年第4期26卷 446-453页

作者： ZHANG Lalu Xiangxiang Dong YAO Lixiu CAI Yunze Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai200240China Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong UniversityShanghai200240China

Existing coupled distributed estimation and motion control strategies of mobile sensor networks present limitations in velocity-varying target tracking. Therefore, a velocity-varying target tracking algorithm based on flocking control is proposed herein. The Kalman-consensus filter is utilized to estimate the position, velocity and acceleration of a target. The flocking control algorithm with a velocity-varying virtual leader enables the position of the center of the mobile sensor network to converge to that of the target. By applying an effective cascading Lyapunov method, stability analysis is performed. Simulation results are provided to validate the feasibility of the proposed algorithm.

关键词： mobile sensor network velocity-varying target tracking flocking control Kalman-consensus filtering

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The Applications of Generalized Computing in Decision-making

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Journal of Systems Science and Systems Engineering 2001年第4期13卷 397-402页

作者： YAO Min, HUANG Yan-jun 1. Dopt. of Computer, Zhejiang University, Hangzhou 3l0028, China key laboratory of education Mnistry for image processing and intelligent control 2. School of Economics, Zhejianig University, Hangzhou 310028, China Dept. of Computer Zhejiang University Hangzhou 310028 China Key Laboratory of Education Ministry for Image Processing and Intelligent Control School of Economics Zhejianig University Hangzhou 310028 China

Knowledge is one of the most important elements in production and the first resource in enterprise. By introducing knowledge to decision making, this paper presents a kind of know1edge decision- making model (KDM for ... 详细信息

关键词： know1edge decision-making generalized computing

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Multi-Human Pose Estimation by Deep Learning-Based Sequential Approach for Human keypoint Position and Human Body Detection

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Journal of Shanghai Jiaotong University (Science) 2023年 1-11页

作者： Tahir, Rizwan Cai, Yunze Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

Recent multimedia and computer vision research has focused on analyzing human behavior and activity using images. Skeleton estimation, known as pose estimation, has received a significant attention. For human pose estimation, deep learning approaches primarily emphasize on the keypoint features. Conversely, in the case of occluded or incomplete poses, the keypoint feature is insufficiently substantial, especially when there are multiple humans in a single frame. Other features, such as the body border and visibility conditions, can contribute to pose estimation in addition to the keypoint feature. Our model framework integrates multiple features, namely the human body mask features, which can serve as a constraint to keypoint location estimation, the body keypoint features, and the keypoint visibility via mask region-based convolutional neural network (Mask-RCNN). A sequential multi-feature learning setup is formed to share multi-features across the structure, whereas, in the Mask-RCNN, the only feature that could be shared through the system is the region of interest feature. By two-way up-scaling with the shared weight process to produce the mask, we have addressed the problems of improper segmentation, small intrusion, and object loss when Mask-RCNN is used, for instance, segmentation. Accuracy is indicated by the percentage of correct keypoint, and our model can identify 86.1% of the correct keypoints. © 2023, Shanghai Jiao Tong University.

关键词： Convolutional neural networks

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Selective Bokeh Effect Transformation

Selective Bokeh Effect Transformation

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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Peng, Juewen Pan, Zhiyu Liu, Chengxin Luo, Xianrui Sun, Huiqiang Shen, Liao Xian, Ke Cao, Zhiguo Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control China Nanyang Technological University S-Lab Singapore

ISBN: (纸本)9798350302493

Bokeh effect transformation is a novel task in computer vision and computational photography. It aims to convert bokeh effects from one camera lens to another. To this end, we introduce a new concept of blur ratio, which represents the ratio of the blur amount of a target image to that of a source image, and propose a novel framework SBTNet based on this concept. For cat-eye simulation and lens type transformation, a two-channel coordinate map and a two-channel one-hot map are added as extra inputs. The core of the framework is a sequence of parallel FeaNets, along with a feature selection and integration strategy, which aims to transform the blur amount with arbitrary blur ratio. The effectiveness of the proposed framework is demonstrated through extensive experiments, and our solution has achieved the top LPIPS metric in NTIRE 2023 Bokeh Effect Transformation Challenge. © 2023 IEEE.

关键词： Color photography

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Region of interest image encryption method based on panoramic segmentation and a novel coupled chaotic map

Region of interest image encryption method based on panorami...

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2022 International Conference on Artificial Intelligence, Virtual Reality, and Visualization, AIVRV 2022

作者： Zhang, Hangming Hu, Hanping School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan430074 China

ISBN: (纸本)9781510662988

Social media is a platform for people to share their lives and interact with others. image sharing is an integral component. Privacy information will inevitably be compromised during the process of sharing whole photos. Sometimes, it is not even caused by the person who shares the image but the third party who forwards the image. In the majority of cases, we do not attempt to protect the entirety of the media;rather, we seek to protect the most crucial portion, whether it is the background or specific objects, which decreasing superfluous cryptography procedures. Unfortunately, current research on such field is extremely rare. In this research, we established a novel pixel-level image encryption technique relying on Panoptic FCN panoramic segmentation and chaos for client-intended images on social media sites. Our suggested technology is capable of automated picture encryption on either the whole images or user-selected areas, whether they are rectangular or irregular, which is suited for all region of interest (ROI) encryption. Relying on a novel coupled chaotic map, this universal new encryption method flattens the array of the image ROI into a series of pixels. The module of Panoptic FCN can be replaced by any other panoptic segmentation models which are stronger in performance. Statistical and cryptographic evaluations demonstrate that our technique preserves the high efficiency for practical applications. © 2023 SPIE. All rights reserved.

关键词： Cryptography

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