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2010 9th International Conference on Information Technology Based Higher Education and Training, ITHET 2010

作者： Hetthéssy, Jeno Barta, András Bars, Ruth Keviczky, László Dept. of Automation and Applied Informatics Budapest University of Technology and Economics HAS-BME Control Research Group Budapest Hungary MTA SZTAKI Computer and Automation Research Institute Hungarian Academy of Sciences Budapest Hungary

ISBN: (纸本)9781424457922

Course material of basic control theory has been overviewed and updated recently at the Faculty of Electrical Engineering and informatics, BME. The paper describes shortly the contents and the teaching methods of the course. In the theoretical material the concept of the Youla parametrization has been introduced which gives a new insight into controller design. MATLAB exercises support understanding and interactively applying the theoretical knowledge. New lecture notes were written both for the theoretical material and for the MATLAB laboratory exercises. The course web-site provides the actual information and gives also additional learning materials. ©2010 IEEE.

关键词： Websites

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Towards a Nex-Gen cottage industry in the digital age: Insights from an action research with rural artisans in India 2

Towards a Nex-Gen cottage industry in the digital age: Insig...

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22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018

作者： Parthiban, Rishikesan Bandyopadhyay, Somprakash Basak, Jayanta Social Informatics Research Group Indian Institute of Management Calcutta Joka D H Road Kolkata700104 India Computer Application Center Heritage Institute of Technology East Kolkata Township Kolkata700107 India

ISBN: (纸本)9784902590838

Despite the recognition of the significance of the crafts industry for inclusive development, its informal, disaggregated and disenfranchised nature poses several problems for the rural artisans, who are often forced to live in poverty. Extant approaches to address the industry's problems have involved siloed attempts, wherein interventions were appropriated to resolve issues within parts of the supply chain, resulting in persistence of the issues. Using Self-Help-group women in rural India as a case in point, the paper adopts a discovery orientation and action research alignment to evolve the design principles of an ICT driven peer-to-peer collaborative, decentralized supply chain model known as Nex-Gen Cottage Industry as a means to organise the industry. The results of a pre-pilot study in a village Kandi have been discussed along with the implications of this research for academia and the society. © PACIS 2018.

关键词： Rural areas

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Combining shape-based and gradient-based classifiers for vehicle classification

Combining shape-based and gradient-based classifiers for veh...

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International IEEE Conference on Intelligent Transportation Systems

作者： Hakki Can Karaimer Ibrahim Cinaroglu Yalin Bastanlar Computer Vision Research Group Dept. of Computer Engineering Izmir Institute of Technology Izmir Turkey

ISBN: (纸本)9781467365970

In this paper, we present our work on vehicle classification with omnidirectional cameras. In particular, we investigate whether the combined use of shape-based and gradient-based classifiers outperforms the individual classifiers or not. For shape-based classification, we extract features from the silhouettes in the omnidirectional video frames, which are obtained after background subtraction. Classification is performed with kNN (k Nearest Neighbors) method, which has been commonly used in shape-based vehicle classification studies in the past. For gradient-based classification, we employ HOG (Histogram of Oriented Gradients) features. Instead of searching a whole video frame, we extract the features in the region located by the foreground silhouette. We use SVM (Support Vector Machines) as the classifier since HOG+SVM is a commonly used pair in visual object detection. The vehicle types that we worked on are motorcycle, car and van (minibus). In experiments, we first analyze the performances of shape-based and HOG-based classifiers separately. Then, we analyze the performance of the combined classifier where the two classifiers are fused at decision level. Results show that the combined classifier is superior to the individual classifiers.

关键词： vehicle classification shape-based classification gradient-based classification histogram of oriented gradients combined classifier omnidirectional cameras Vehicle classification Classifiers Plane Figure

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Multi-modal region selection approach for training object detectors 12

Multi-modal region selection approach for training object de...

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2nd ACM International Conference on Multimedia Retrieval, ICMR 2012

作者： Chatzilari, Elisavet Nikolopoulos, Spiros Kompatsiaris, Yiannis Kittler, Josef Centre for Research and Technology Hellas Informatics and Telematics Institute Greece Centre for Vision Speech and Signal Processing University of Surrey Guildford United Kingdom School of Electronic Engineering and Computer Science QueenMary University of London United Kingdom

ISBN: (纸本)9781450313292

Our purpose in this work is to boost the performance of object classifiers learned using the self-training paradigm. We exploit the multi-modal nature of tagged images found in social networks, to optimize the process of region selection when retraining the initial model. More specifically, the proposed approach uses a small number of manually labelled regions to train the initial object detection classifiers. Then, a large number of loosely tagged images, pre-segmented by an automatic segmentation algorithm, is used to enhance the initial training set with additional image regions. However, in contrast to the typical case of self-training where the image regions are selected based solely on how well they fit to the original classification model, our approach aims at optimizing this selection by making combined use of both visual and textual information. The experimental results show that the object detection classifiers generated using the proposed approach outperform the classifiers generated using the typical self-training paradigm. Copyright © 2012 ACM.

关键词： Object detection

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Classification of Chicken Meat Freshness using Convolutional Neural Network Algorithms

Classification of Chicken Meat Freshness using Convolutional...

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International Conference on Innovation and Intelligence for informatics, Computing, and Technologies (3ICT)

作者： Calvin Ghiri Basuki Putra Esa Prakasa Departement of Electrical Engineering Universitas Bangka Belitung Pangkalpinang Indonesia Computer Vision Research Group Research Center of Informatics Indonesian Institute of Sciences (LIPI) Bandung Indonesia

ISBN: (数字)9781728196732

ISBN: (纸本)9781728196749

Broiler chicken meat is one of the most widely consumed meat types in Indonesia, this high level of consumption makes a lot of consumer demand in the market. However, there was a found seller who sells broiler chicken meat that are rotten. In this study, we develop chicken meat freshness identification using a convolutional neural network algorithm. This study used the image dataset of broiler chicken breasts. There are two categories of chicken meat used in the study, namely, fresh and rotten. The meat images were acquired by using a smartphone camera. For the process of cropping chicken meat images, we use thresholding with the Otsu method and conversion of RGB images to binary images to select the area of RGB images before cropping the images. The chicken meat images were cropped into three sizes and then used as a dataset in the study. The chicken meat image dataset was trained using a simple architecture that was self-made called Ayam6Net, we also used the AlexNet, VGGNet, and GoogLeNet architectures as a comparison. Ayam6Net has the highest accuracy of 92.9%. From the experiment results, we can conclude that using Ayam6Net architecture with dataset $400\times 400$ pixels has a better accuracy result compared with other architectures and other sizes image datasets.

关键词： computer architecture Training informatics Feature extraction Technological innovation Gas detectors Image color analysis

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S/G light-tree: Multicast grooming architecture for improved resource allocation

S/G light-tree: Multicast grooming architecture for improved...

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ONDM 2008 - 12th Conference on Optical Network Design and Modelling

作者： Sierra, Javier E. Caro, Luis F. Solano, Fernando Fabregat, Ramon Donoso, Yezid GIDATI Research Group Universidad Pontificia Bolivariana Medellin Colombia Institute of Informatics and Applications University of Girona Girona Spain Computer Science Department Universidad de Los Andes Bogota Colombia

ISBN: (纸本)9783901882272

Internet traffic demands are constantly increasing and a considerable amount of this increase is expected to be of multicast type. Optical Transport Networks (OTN) must be prepared in terms of better resource utilization for accommodating multicast traffic. For this purpose multicast traffic grooming has been considered. Light-trees have been proposed for supporting multicast connections in OTN. Nevertheless when light-trees are used with traffic grooming, resources can be overutilized as traffic can be routed to undesirable destinations in order to avoid Optical-Electrical-Optical (OEO) conversions. In this paper a novel architecture named S/G Light-tree for supporting multicast connections is proposed. The architecture allows to eliminate and aggregate traffic in different wavelengths without performing OEO conversions. The architecture uses labels supported by Generalized Multiprotocol Label Switching (GMPLS). A heuristic that routes traffic demands using less wavelengths by taking advantage of the proposed architecture is designed as well. Simulation results show that the architecture can minimize the number of used wavelengths and OEO conversions when compared to light-trees.

关键词： Forestry

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Semi-supervised object recognition using flickr images

Semi-supervised object recognition using flickr images

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International Workshop on Content-Based Multimedia Indexing

作者： Chatzilari, Elisavet Nikolopoulos, Spiros Papadopoulos, Symeon Zigkolis, Christos Kompatsiaris, Yiannis Centre for Research and Technology Hellas Informatics and Telematics Institute Greece Centre for Vision Speech and Signal Processing University of Surrey Guildford United Kingdom School of Electronic Engineering and Computer Science QueenMary University of London United Kingdom Aristotle University Department of Informatics 54124 Thessaloniki Greece

ISBN: (纸本)9781612844336

In this work we present an algorithm for extracting region level annotations from flickr images using a small set of manually labelled regions to guide the selection process. More specifically, we construct a set of flickr images that focuses on a certain concept and apply a novel graph based clustering algorithm on their regions. Then, we select the cluster or clusters that correspond to the examined concept guided by the manually labelled data. Experimental results show that although the obtained regions are of lower quality compared to the manually labelled regions, the gain in effort compensates for the loss in performance. © 2011 IEEE.

关键词： Object recognition

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The role of systems thinking in diffusion of new technologies

The role of systems thinking in diffusion of new technologie...

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IEE Colloquium on Advances in Systems Engineering Tools and their Environments

作者： G.J. Awcock Computer Vision Systems Group Information Technology Research Institute Brighton Polytechnic UK

This paper represents a personal view of the influence that systems awareness has, or more correctly should have, in the successful transition of new technology from its research base to the full achievement of its utilisation potential within industry. This view has been developed during the study of the application of computer vision systems to industry, so this field of technology is used as an exemplar, but it is believed that the points raised are of more general importance.< >

关键词： Machine vision Systems engineering

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Implementation of a Real-Time Target Tracking Behaviour Using Video Sensors

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IFAC Proceedings Volumes 2001年第7期34卷 517-521页

作者： V. lla P. Ridao J.De La Cruz J. Batlle Computer Vision and Robotics Group Institute of Informatics and Applications. University of Girona Edifici Politecnica ll Campus Montilivi 17071 Girona Spain

Using software OS, real-time operation is constrained by acquisition and preprocessing tasks of input signals. In this way, this paper presents an implementation of a real time target tracking behaviour, from snapped images of the environment, as an example of how to take advantage of real-time hardware devices as a helpful systems for control architectures. A specific board based on FPGA/DSP processors has been used in order to reach this goal. The system has been thought for a marine and underwater environment and it has been tested using GARBI autonomous underwater vehicle. The implemented behaviours allow the robot to navigate autonomously and follow a diver.

关键词： behaviour binary image autonomous vehicle computer control

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Comparison of self-similarity measures for multi-modal non-rigid registration of 3D-PLI brain images

Comparison of self-similarity measures for multi-modal non-r...

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Workshop on Bildverarbeitung fur die Medizin, 2018

作者： Ali, Sharib Lin, Dehui Axer, Markus Rohr, Karl Department of Bioinformatics and Functional Genomics Biomedical Computer Vision Group BIOQUANT IPMB DKFZ University of Heidelberg Heidelberg Germany Institute of Neuroscience and Medicine 1 Research Centre Jülich Jülich Germany

ISBN: (纸本)9783662580950

We introduce self-similarity measures in a spline-based nonrigid registration method. We applied our method to register multimodal 3D polarized light imaging and blockface image data of human and rat brain sections. Quantitative evaluations demonstrate that using self-similarity measures increases the accuracy and robustness compared to a traditional mutual information measure. © Springer-Verlag GmbH Deutschland 2018.

关键词： Brain mapping

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