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1st IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2011

作者： Kim, Donggyun Kim, Seonyung Paik, Joonki Jung, Junghoon Kim, Taechan Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of System LSI Samsung Electronics Co. Ltd. Suwon Korea Republic of

ISBN: (纸本)9781457702341

In this paper, we propose a peripheral region enhancement method for geometrically compensated images from a fisheye lens. The proposed method provides a novel filtering method based on the degradation model of a fisheye lens. More specifically, we first present a space-variant image degradation model using generic Gaussian function with geometric distortion. We then apply the truncated constraint least squares (TCLS) filter for restoring the peripheral region of the image in the real-time, space-adaptive manner. Experimental results demonstrate that the proposed method can enhance the peripheral region while keeping the high-quality center region. © 2011 IEEE.

关键词： image enhancement

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A Memristive Spiking Neural Network Circuit for Bio-inspired Navigation Based on Spatial Cognitive Mechanisms

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IEEE Transactions on Biomedical Circuits and systems 2024年第3期19卷 686-698页

作者： Chen, Zhanfei Wang, Xiaoping Wang, Zilu Yang, Chao Huang, Tingwen Lai, Jingang Zeng, Zhigang School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation China Hubei Key Laboratory of Brain-inspired Intelligent Systems Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Guangxi University of Science and Technology School of Computer Science and Technology Liuzhou545006 China Shenzhen University of Advanced Technology School of Computer Science and Control Engineering Shenzhen518055 China

Cognitive navigation,a high-level and crucial function for organisms' survival in nature,enables autonomous exploration and navigation within the environment. However,most existing works for bio-inspired navigation are implemented with non-neuromorphic computing. This work proposes a bio-inspired memristive spiking neural network (SNN) circuit for goal-oriented navigation,capable of online decision-making through reward-based learning. The circuit comprises three primary modules. The place cell module encodes the agent's spatial position in real-time through Poisson spiking;the action cell module determines the direction of subsequent movement;and the reward-based learning module provides a bio-inspired learning method adaptive to delayed and sparse rewards. To facilitate practical application,the entire SNN is quantized and deployed on a real memristive hardware platform,achieving about a 21× reduction in energy consumption compared to a typical digital acceleration system in the forward computing phase. This work offers an implementation idea of neuromorphic solution for robotic navigation application in low-power scenarios. © 2007-2012 IEEE.

关键词： intelligent robots

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Robust feature detection using particle keypoints and its application to video stabilization in a consumer handheld camera

Robust feature detection using particle keypoints and its ap...

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IEEE International Conference on Consumer Electronics, ICCE 2016

作者： Jeon, Semi Yoon, Inhye Yang, Seung'I Kim, Bongmo Kim, Jisung Paik, Joonki Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of Video Technology Lab. Future Technology RandD Division SK Telecom Korea Republic of

ISBN: (纸本)9781467383646

Compact, portable digital cameras have been popular to consumers. This paper presents a robust feature detection method using particle keypoints and its application to video stabilization. The proposed video stabilization algorithm consists of three steps: i) generation of a flat region map based on the Gaussian filter, ii) robust feature point detection using particle keypoints, and iii) camera paths estimation for enhancing a shaky video. As a result, the proposed algorithm can estimate optimal homography by redefining important feature points using particle keypoints in the flat region map. The proposed robust feature detection algorithm is suitable for enhancing the quality of video acquired by consumer handheld imaging devices. © 2016 IEEE.

关键词： Stabilization

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A Wearable Finger Exoskeleton Based on the Crank-Rocker Mechanism for Rehabilitation 29

A Wearable Finger Exoskeleton Based on the Crank-Rocker Mech...

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29th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2018

作者： Ke, Ang Huang, Jian Chen, Luyao He, Jiping Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Luoyu Road 1037 Wuhan Hubei China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology 5 South Zhongguancun Street Beijing China

ISBN: (纸本)9781538667927

Rehabilitation of the grasp function of hands is critical for improving the quality of living for those who suffer from lost or weakened hand abilities due to neuromuscular disease. Current finger rehabilitation devices usually need a complex mechanical structure or a larger actuation system, which reduce the portability of the devices for daily living rehabilitation. In this work, we introduced the developing an ultra-light integrated modular finger exoskeleton that driven by a crank-rocker mechanism. The actuator for each joint is directly assembled at each joint by simplifying the structure design, which makes the device portable for patients. All of the parts are manufactured by 3D printing thus to reduce the initial moment of the whole device, the actuator we used is also the ultra-light server motor. The weight of the whole device is just about 60g (including 3 actuators). We analysised the kinematic of the exoskeleton, then a real-Time embedded position tracking control algorithm is implemented on an Arduino board, which is used as the controller. Experimental results show that our device is capable of both positive and active training for finger habilitation. © 2018 IEEE.

关键词： Actuators

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Multiresolution Object Recognition Using Dual Heuristic Programming

Multiresolution Object Recognition Using Dual Heuristic Prog...

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International Joint Conference on Neural Networks (IJCNN)

作者： F. Siddiqui K.M. Iftekharuddin Intelligent Systems and Image Processing Laboratory Department of Electrical and Computer Engineering University of Memphis Memphis TN USA

We present automatic target recognition (ATR) model based on principles of biological vision systems. The model employs reinforcement learning (RL) through Dual Heuristic Programming (DHP). The performance of the reported ATR model is compared to that of our previously reported ATR model, based on Heuristic Dynamic Programming (HDP). The HDP and DHP, known as the Adaptive Critic Designs (ACD), are neural network based implementation of Dynamic Programming (DP). The simulation shows promising results for both HDP and DHP based ATR model in presence of resolution distortion in incoming images and confirms that the DHP model is faster and more robust for our ATR system than the HDP.

关键词： Object recognition Learning Robustness Biological system modeling Machine vision Target recognition Dynamic programming Neural networks image resolution Nonlinear distortion

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Wavelet based estimation of the fractal dimension in fBm images

Wavelet based estimation of the fractal dimension in fBm ima...

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International IEEE/EMBS Conference on Neural Engineering, CNE

作者： C. Parra K. Iftekharuddin D. Rendon Intelligent Systems and Image Processing Laboratory Department of Electrical and Computer Engineering University of Memphis Memphis TN USA

Fractional Brownian Motion (fBm) has been successfully exploited to model an important number of physical phenomena and non-stationary processes such as medical images. These mathematical models closely describe essential properties of natural phenomena, such as self-similarity, scale invariance and fractal dimension (FD). The use of wavelet analysis combined with fBm analysis may provide an interesting approach to compute key values for fBm processes, such as the fractal dimension FD. We propose two models to calculate the Hurst Coefficient H (and hence FD) for both one-dimensional and two-dimensional signals. The first approach is based on statistical properties of the signals, while the second one is based on their spectral characteristics. A formal extension of these two models to 2D processes is developed and implemented, and a comparison of both is presented. The proposed algorithms are tested using tomographic brain tumor data. Our simulation experiments offer promising results in the identification of such lesions.

关键词： Fractals Signal analysis Brownian motion Biomedical imaging Mathematical model Wavelet analysis Signal processing Testing Tomography Neoplasms

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A Modified E-Shaped Compact Printed Antenna for 28 GHz 5G Applications 6th

A Modified E-Shaped Compact Printed Antenna for 28 GHz 5G A...

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6th International Conference on Wireless Technologies, Embedded and intelligent systems, WITS 2020

作者： Ghazaoui, Yousra El Alami, Ali Das, Sudipta El Ghzaoui, Mohammed Intelligent Systems Networks and Telecommunications Team IMAGE Laboratory EST-UMI Meknes Morocco Faculty of Sciences and Technics Renewable Energies Information Processing and Transmission Laboratory Moulay Ismail University Errachidia Morocco Department of Electronics and Communication Engineering IMPS College of Engineering and Technology Malda India

ISBN: (纸本)9789813368927

A single band printed antenna with a modified E-shaped structure is proposed for 5G applications at 28 GHz band. The suggested antenna has been constructed on a 5.5 × 4.35 mm2 FR-4 substrate (Εr= 4.4 and h= 1.6 mm ) through slot loading technique. The incorporation of rectangular and tiny square shaped slots has improved the resonance and radiation characteristics of the designed antenna. The wide operating bandwidth of the suggested antenna covers 25.99–29.88 GHz frequency spectrum to support 28 GHz 5G applications. The presented antenna depicts low mismatch loss and thus better impedance matching offering a reflection coefficient of about −40.88 dB at 28 GHz. The proposed antenna offers desired radiation patterns (E and H planes) with a peak gain of about 5.64 dBi at 28 GHz. Furthermore, an extensive analysis of VSWR, input impedance, and surface current distribution are also presented to explain the working functionality of the suggested antenna. The proposed structure is a preferable choice for 28 GHz 5G applications due to its compact size and high performance parameters and it covers the bandwidth requirements of 5G applications at 28 GHz. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Microstrip antennas

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An ant colony optimization routing algorithm for two order pickers with congestion consideration

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Computers & Industrial Engineering 2013年第1期66卷 77-85页

作者： Fangyu Chen Hongwei Wang Chao Qi Yong Xie Key Laboratory of Image Processing and Intelligent Control Institute of Systems Engineering Huazhong University of Science & Technology Hubei Wuhan 430074 People’s Republic of China

This paper develops a routing method to control the picker congestion that challenges the traditional assumption regarding the narrow-aisle order picking system. We proposes a new routing algorithm based on Ant Colony Optimization (ACO) for two order pickers (A-TOP) with congestion consideration. Using two extended dedicated heuristics with congestion consideration as reference group, a comprehensive simulation study is conducted to evaluate the effectiveness of A-TOP. The simulation proves that A-TOP achieves the shortest total picking time in most instances and performs well in dealing with the congestion. The impacts of warehouse layout, order size, and pick:walk-time ratio on A-TOP and system performance are analyzed as well. A-TOP can adapt to different warehouse configurations, meanwhile, it can be easily extended to the situation with more than two order pickers.

关键词： Routing method Order picking Ant colony optimization Congestion Warehouse management

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Ethnicity classification based on gait using multi-view fusion

Ethnicity classification based on gait using multi-view fusi...

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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： De Zhang Yunhong Wang Bir Bhanu Center for Research in Intelligent Systems University of California Riverside CA USA Intelligent Recognition and Image Processing Laboratory Beihang University Beijing China

The determination of ethnicity of an individual, as a soft biometrics, can be very useful in a video-based surveillance system. Currently, face is commonly used to determine the ethnicity of a person. Up to now, gait has been used for individual recognition and gender classification but not for ethnicity determination. This paper focuses on the ethnicity determination based on fusion of multi-view gait. Gait Energy image (GEI) is used to analyze the recognition power of gait for ethnicity. Feature fusion, score fusion and decision fusion from multiple views of gait are explored. For the feature fusion, GEI images and camera views are put together to render a third-order tensor (x; y; view). A multilinear principal component analysis (MPCA) is used to extract features from tensor objects which integrate all views. For the score fusion, the similarity scores measured from single views are combined with a weighted SUM rule. For the decision fusion, ethnicity classification is realized on each individual view first. The classification results are then combined to make the final determination with a majority vote rule. A database of 36 walking people (East Asian and South American) was acquired from 7 different camera views. The experimental results show that ethnicity can be determined from human gait in video automatically. The classification rate is improved by fusing multiple camera views and a comparison among different fusion schemes shows that the MPCA based feature fusion performs the best.

关键词： Cameras Tensile stress Biometrics Surveillance image analysis image recognition Rendering (computer graphics) Principal component analysis Feature extraction Voting

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An Approach with Nested Partition for Resource-Constrained Project Scheduling Problem

An Approach with Nested Partition for Resource-Constrained P...

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2012 IEEE 19th International Conference on Industrial Engineering and Engineering Management(IE&EM 2012)

作者： Zhen-yuan Liu Wen-min Yu Institute of Systems Engineering Huazhong University of Science and Technology Key Laboratory of Education Ministry for Image Processing and Intelligent Control

A time-based nested partition （NP） approach is proposed to solve resource-constrained project scheduling problem （RCPSP） in this paper. In iteration, one activity is selected as the base point of which the finish time interval calculated by CPM is divided into two parts to form two subregions on the basis of the promising region of the last iteration. Then sampling is taken in both subregions and the surrounding region to determine the promising region and aggregate the other as the surrounding region of this iteration so that whether the backtracking or the moving operation being performed is determined. Double justification is also performed in iteration to improve the results. The results of numerical tests on PSPLIB show the effectiveness and time-efficient of the proposed NP method.

关键词： Double justification nested partition RCPSP sampling

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