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检索条件"任意字段=1st International Conference on Image Processing Machine Learning and Pattern Recognition"

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Environment recognition for Navigation of Autonomous Wheelchair from a Video image 17

Environment Recognition for Navigation of Autonomous Wheelch...

引用

17th international conference on Control, Automation and Systems (ICCAS)

作者： Nakayama, Yoshiki Lu, Huimin Tan, Joo Kooi Kim, Hyoungseop Kyushu Inst Technol 1-1 Sensui Kitakyushu Fukuoka 8048550 Japan

ISBN: (纸本)9788993215144

The Japanese population has rapidly aged and the number of aged persons who have lower physical ability has increased recently. Thus the development of medical and healthcare devices is expected. Wheelchair requires care support in most cases. Therefore the development of autonomous wheelchair is meaningful since we can expect to improve convenience and to reduce burden of caregivers. The autonomous wheelchair requires several techniques. Our research is to develop a navigation system based on image processing techniques. However, we assume that the system instructs an appropriate direction to head towards the destination when a wheelchair user comes to a crossing. Incidentally, deep learning, a kind of artificial neural network, has attracted attention in the field of machine learning in recent years. This paper proposes methodology for supporting autonomous driving by use of a classifier trained on a video images with deep learning. Also, we apply visual odometry to generate training data.

关键词： Autonomous Wheelchair Monocular Camera Place recognition Convolutional Neural Network Visual Odometry

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Proceedings of the international conference on Document Analysis and recognition, ICDAR

Proceedings of the International Conference on Document Anal...

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1st international Workshop on Human-Document Interaction, HDI 2017

ISBN: (纸本)9781538635865

The proceedings contain 314 papers. The topics discussed include: pyramidal stochastic graphlet embedding for document pattern classification;image operator learning coupled with CNN classification and its application to staff line removal;a complete scheme of spatially categorized glyph recognition for the transliteration of Balinese palm leaf manuscripts;early recognition of handwritten gestures based on multi-classifier reject option;an efficient combinatorial algorithm for optimal compression of a polyline with segments and arcs;the graphic narrative corpus (GNC): design, annotation, and analysis for the digital humanities;segmentation-free speech text recognition for comic books;an overview of comics research in computer science;Transkribus - a service platform for transcription, recognition and retrieval of historical documents;DAE-NG: a shareable and open document image annotation data framework;guiding text image keypoints extraction through layout analysis;click-free, video-based document capture - methodology and evaluation;human-assisted signature recognition based on comparative attributes;cognitive state measurement on learning materials by utilizing eye tracker and thermal camera;deep convolutional recurrent network for segmentation-free offline handwritten Japanese text recognition;KHATT: a deep learning benchmark on Arabic script;multilevel context representation for improving object recognition;semantic text encoding for text classification using convolutional neural networks;a case study of the relationship between local pen action and three dimensional shapes of handwritten strokes;and robustness of character recognition techniques to double print-and-scan process.

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Proceedings of the international conference on Document Analysis and recognition, ICDAR

Proceedings of the International Conference on Document Anal...

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1st international Workshop on Open Services and Tools for Document Analysis, ICDAR-Ost 2017

ISBN: (纸本)9781538635865

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Proceedings of the international conference on Document Analysis and recognition, ICDAR

Proceedings of the International Conference on Document Anal...

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1st international Workshop on Computational Document Forensics, IWCDF 2017

ISBN: (纸本)9781538635865

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Gesture Modelling and recognition by Integrating Declarative Models and pattern recognition Algorithms 19th

Gesture Modelling and Recognition by Integrating Declarative...

引用

19th international conference on image Analysis and processing (ICIAP)

作者： Carcangiu, Alessandro Spano, Lucio Davide Fumera, Giorgio Roli, Fabio Univ Cagliari Dept Elect & Elect Engn I-09123 Cagliari Italy Univ Cagliari Dept Math & Comp Sci I-09124 Cagliari Italy

ISBN: (纸本)9783319685601;9783319685595

Gesture recognition approaches based on computer vision and machine learning mainly focus on recognition accuracy and robustness. Research on user interface development focuses instead on the orthogonal problem of providing guidance for performing and discovering interactive gestures, through compositional approaches that provide information on gesture sub-parts. We make a first step toward combining the advantages of both approaches. We introduce DEICTIC, a compositional and declarative gesture description model which uses basic Hidden Markov Models (HMMs) to recognize meaningful pre-defined primitives (gesture sub-parts), and uses a composition of basic HMMs to recognize complex gestures. Preliminary empirical results show that DEICTIC exhibits a similar recognition performance as "monolithic" HMMs used in state-of-the-art vision-based approaches, retaining at the same time the advantages of declarative approaches.

关键词： Gesture recognition Hidden Markov Models Compositional Declarative

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Depth from Defocus via Active Quasi-random Point Projections: A Deep learning Approach 14th

Depth from Defocus via Active Quasi-random Point Projections...

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14th international conference on image Analysis and recognition (ICIAR)

作者： Ma, Avery Wong, Alexander Clausi, David Univ Waterloo Vis & Image Proc Lab Syst Design Engn East Campus 4295 Phillip St Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9783319598765;9783319598758

Depth estimation plays an important role in many computer vision and computer graphics applications. Existing depth measurement techniques are still complex and restrictive. In this paper, we present a novel technique for inferring depth measurements via depth from defocus using active quasi-random point projection patterns. A quasi-random point projection pattern is projected onto the scene of interest, and each projection point in the image captured by a cellphone camera is analyzed using a deep learning model to estimate the depth at that point. The proposed method has a relatively simple setup, consisting of a camera and a projector, and enables depth inference from a single capture. We evaluate the proposed method both quantitatively and qualitatively and demonstrate strong potential for simple and efficient depth sensing.

关键词： Depth from defocus Convolutional neural network 3D reconstruction Depth sensing

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Crowd Disaster Avoidance System (CDAS) by Deep learning Using eXtended Center Symmetric Local Binary pattern (XCS-LBP) Texture Features

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1st international conference on Computer Vision and image processing (CVIP)

作者： Nagananthini, C. Yogameena, B. Thiagarajar Coll Engn Dept ECE Madurai Tamil Nadu India

ISBN: (纸本)9789811021046;9789811021039

In order to avoid crowd disaster in public gatherings, this paper aims to develop an efficient algorithm that works well in both indoor and outdoor scenes to give early warning message automatically. It also deals with high dense crowd and sudden illumination changing environment. To address this problem, first an XCS-LBP (eXtended Center Symmetric Local Binary pattern) features are extracted which works well under sudden illumination changes. Subsequently, these features are trained using deep Convolutional Neural Network (CNN) for crowd count. Finally, a warning message is displayed to the authority, if the people count exceeds a certain limit in order to avoid the crowd disaster in advance. Benchmark datasets such as PETS2009, UCSD and UFC_CC_50 have been used for experimentation. The performance measures such as MSE (Mean Square Error), MESA (Maximum Excess over Sub Arrays) and MAE (Mean Absolute Error) have been calculated and the proposed approach provides high accuracy.

关键词： Crowd disaster Texture feature Convolutional neural network People counting

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Synthesis of a Neural Network Classifier for Hepatocellular Carcinoma Grading Based on Triphasic CT images 1st

Synthesis of a Neural Network Classifier for Hepatocellular ...

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1st international conference on Recent Trends in image processing and pattern recognition (RTIP2R)

作者： Bevilacqua, Vitoantonio Carnimeo, Leonarda Brunetti, Antonio De Pace, Andrea Galeandro, Pietro Trotta, Gianpaolo Francesco Caporusso, Nicholas Marino, Francescomaria Alberotanza, Vito Scardapane, Arnaldo Polytech Bari Dept Elect & Informat Engn Via Orabona 4 I-70125 Bari Italy Polytech Bari Dept Mech & Management Engn Via Orabona 4 I-70125 Bari Italy Univ Bari Aldo Moro Sect Diagnost Imaging Interdisciplinary Dept Med Piazza Giulio Cesare 11 I-70120 Bari Italy

ISBN: (纸本)9789811048593;9789811048586

Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grading Hepatocellular carcinoma (HCC) by means of Computed Tomography (CT) images, avoiding that patient undergo any medical invasive procedures such as biopsies. The individuation and characterization of Regions of Interest (ROIs) containing lesions is an important phase that enables an easier classification between two classes of HCCs. Two phases are needed for the individuation of lesioned ROIs: a liver isolation in each CT slice, and a lesion segmentation. Ultimately, all individuated ROIs are described by morphological features and, finally, a feed-forward supervised Artificial Neural Network (ANN) is used to classify them. Testing determined that the ANN topologies found through an evolutionary strategy showed a high generalization on the mean performance indices regardless of applied training, validation and test sets, showing good performances in terms of both accuracy and sensitivity, permitting a correct grading of HCC lesions.

关键词： Hepatocellular carcinoma Computed Tomography image processing Artificial Neural Network Genetic Algorithm

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Proposal of system for automatic weld evaluation 21

Proposal of system for automatic weld evaluation

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21st international conference on Process Control (PC)

作者： Haffner, Oto Kucera, Erik Kozak, stefan stark, Erich Slovak Univ Technol Bratislava Fac Elect Engn & Informat Technol Bratislava Slovakia

ISBN: (纸本)9781538640111

The paper deals with the development of a system for automatic weld recognition using new information technologies based on cloud computing and single-board computer in the context of Industry 4.0. The proposed system is based on a visual system for weld recognition, and a neural network based on cloud computing for real-time weld evaluation, both implemented on a single-board low-cost computer. The proposed system was successfully verified on welding samples which correspond to a real welding process in the car production process. The system considerably contributes to the welds diagnostics in industrial processes of small-and medium-sized enterprises.

关键词： image processing single-board weld evaluation visual system segmentation entropy IDS uEye XS Raspberry Pi 2 Microsoft Azure machine learning Industry 4.0

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1st international conference on Advanced Informatics for Computing Research, ICAICR 2017

1st International Conference on Advanced Informatics for Com...

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1st international conference on Advanced Informatics for Computing Research, ICAICR 2017

ISBN: (纸本)9789811057793

The proceedings contain 32 papers. The special focus in this conference is on Advanced Informatics for Computing Research. The topics include: Fuzzy based efficient mechanism for URL assignment in dynamic web crawler;towards filtering of SMS spam messages using machine learning based technique;intelligent computing methods in language processing by brain;classification algorithms for prediction of lumbar spine pathologies;keyword based identification of thrust area using mapreduce for knowledge discovery;an efficient genetic algorithm for fuzzy community detection in social network;priority based service broker policy for fog computing environment;software remodularization by estimating structural and conceptual relations among classes and using hierarchical clustering;requirements traceability through information retrieval using dynamic integration of structural and co-change coupling;bilingual code-mixing in Indian social media texts for Hindi and English;performance evaluation and comparative study of color image segmentation algorithm;electroencephalography based analysis of emotions among Indian film viewers;fuel assembly height measurements at the nuclear power plant unit active zone;a novel approach to segment nucleus of uterine cervix pap smear cells using watershed segmentation;parametric study of various direction of arrival estimation techniques;deep CNN-based method for segmenting lung fields in digital chest radiographs;quality assessment of a job portal system designed using bout design pattern;analyzing factors affecting the performance of data mining tools;stable feature selection with privacy preserving data mining algorithm and an efficient routing protocol for DTN.

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