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

共 1528 条记录，以下是981-990 订阅

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On Analysis of Wheat Leaf Infection by Using image processing 1st

On Analysis of Wheat Leaf Infection by Using Image Processin...

引用

1st international conference on Data Engineering and Communication Technology (ICDECT)

作者： Raichaudhuri, Rittika Sharma, Rashmi Univ Petr & Energy Studies Coll Engn Studies Ctr Informat Technol Dehra Dun India

ISBN: (纸本)9789811016752;9789811016745

In present scenario, agriculture forms a vital part in India's economy. More than 50 % of India's population is dependent (directly or indirectly) on agriculture for their livelihood. In India many crops are cultivated, out of which wheat being one of the most important food grain that this country cultivates and exports. Thus it can be seen that wheat forms a major part of the Indian agricultural system and India's economy. Hence, maintenance of the steady production of above stated crop is very important. The main idea of this project is to provide a system for detecting wheat leaf diseases. The given system will study the leaf image of a wheat plant through image processing and pattern recognition algorithms. Former algorithms are used for extracting vital information from the leaf and the latter is used for detecting the disease that it is infected with. For image processing and segmentation usage of k-means algorithm and canny filter has been suggested. pattern recognition is achieved through PCA or GLCM and classification through SVM or ANN.

关键词： Wheat leaf image processing Probability theory Feature extraction and classification

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machine learning based pattern recognition and Classification Framework Development 17

Machine Learning based Pattern Recognition and Classificatio...

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

作者： Omarov, Batyrkhan Cho, Young Im Gachon Univ Dept Comp Engn Seoul 1342 South Korea

ISBN: (纸本)9788993215144

In this paper we describe implementation of several step pattern recognition framework. pattern recognition is the main aspect for different important areas such as video surveillance, biometrics, interactive game applications, human computer interaction and access control systems. These systems require fast real time detection and recognition with high recognition rate. In this paper we propose implementation of the pattern recognition system. In order to increase recognition rate of the system we apply image preprocessing and neural networks.

关键词： Neural networks recognition image preprocessing

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pattern recognition Based on Hierarchical Description of Decision Rules Using Choquet Integral 1st

Pattern Recognition Based on Hierarchical Description of Dec...

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

作者： Santosh, K. C. Wendling, Laurent Univ South Dakota Dept Comp Sci 414 E Clark St Vermillion SD 57069 USA Univ Paris Descartes Paris V LIPADE 45 Rue St Peres F-75270 Paris 06 France

ISBN: (纸本)9789811048593;9789811048586

A hierarchical approach to automatically extract subsets of soft output classifiers, assumed to decision rules, is presented in this paper. Output of classifiers are aggregated into a decision scheme using the Choquet integral. To handle this, two selection schemes are defined, aiming to discard weak or redundant decision rules so that most relevant subsets are restored. For validation, we have used two different datasets: shapes (Sharvit) and graphical symbols (handwritten, CVC - Barcelona). Our experimental study attests the interest of the proposed methods.

关键词： Choquet integral Selection of decision rules Hierarchical description

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Development of Biometric Palm Vein Trait Based Person recognition System 1

Development of Biometric Palm Vein Trait Based Person Recogn...

引用

1st international conference on Intelligent Systems and Information Management (ICISIM)

作者： Raut, Shriram D. Humbe, V. T. Mane, Arjun V. Solapur Univ Dept Comp Sci Solapur India SRTM Univ Sch Technol Subctr Latur India Govt Inst Forens Sci Dept Digital & Cyber Forens Nagpur Maharashtra India

ISBN: (纸本)9781509042647

Biometric Authentication is the main stream to attract attention of researcher to develop algorithm for data and security concern. The palm vein biometric is emerging as the most promising physiological characteristic to develop efficient recognition system. This paper discuss about the new dimension to generate biometric trait key rather a template free key generation extracted by means of rigorous pattern recognition and information security tactics. The generation of key is exercised through mapping of certain digital image processing operation, distance metric computation and information security policies. The model of recognition system proposed that includes phases such as feature extraction and detection followed by the development of recognition technique based on unique and distinct detected palm vein feature characteristics. The proposed work gives novel and robust algorithm for the recognition of the subject. The experimental work gives result with 99.47% high rate of accuracy for the recognition of the subject.

关键词： Palm vein image filter Edge detection Corner point detector recognition system

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A Hybrid Approach for Hyper Spectral image Segmentation Using SMLR and PSO Optimization 1st

A Hybrid Approach for Hyper Spectral Image Segmentation Usin...

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

作者： Karchi, Rashmi P. Nagesh, B. K. Bharathiar Univ Deaprtment Comp Sci Coimbatore 641046 Tamil Nadu India SIT Dept Comp Sci & Engn Mangalore 574143 Karnataka India

ISBN: (纸本)9789811048593;9789811048586

A hybrid approach for hyperspectral image segmentation is presented in this paper. The contribution of the proposed work is in two folds. First, learning of the class posterior probability distributions with Quadratic Programming or joint probability distribution by employing sparse multinomial logistic regression (SMLR) model. Secondly, estimation of the dependencies using spatial information and edge information by minimum spanning forest rooted on markers by acquiring the information from the first step to segment the hyper spectral image using a Markov Random field segments. The particle swarm optimization (PSO) is performed based on the SMLR posterior probabilities to reduce the large number of training data set. The performance of the proposed approach is illustrated in a number of experimental comparisons with recently introduced hyperspectral image analysis methods using both simulated and real hyper spectral data sets of Mars.

关键词： Feature selection Hyperspectral image classification Particle swarm optimization Spatio-spectral analysis

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Microscopic image Classification Using DCT for the Detection of Acute Lymphoblastic Leukemia (ALL)

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

作者： Mishra, Sonali Sharma, Lokesh Majhi, Bansidhar Sa, Pankaj Kumar Natl Inst Technol Dept Comp Sci & Engn Pattern Recognit Res Lab Rourkela 769008 India

ISBN: (纸本)9789811021046;9789811021039

Development of a computer-aided diagnosis (CAD) system for early detection of leukemia is very essential for the betterment of medical purpose. In recent years, a variety of CAD system has been proposed for the detection of leukemia. Acute leukemia is a malignant neoplastic disorder that influences a larger fraction of world population. In modern medical science, there are sufficient newly formulated methodologies for the early detection of leukemia. Such advanced technologies include medical image processing methods for the detection of the syndrome. This paper shows that use of a highly appropriate feature extraction technique is required for the classification of a disease. In the field of image processing and machine learning approach, Discrete Cosine Transform (DCT) is a well-known technique. Nucleus features are extracted from the RGB image. The proposed method provides an opportunity to fine-tune the accuracy for the detection of the disease. Experimental results using publicly available dataset like ALL-IDB shows the superiority of the proposed method with SVM classifier comparing it with some other standard classifiers.

关键词： Acute Lymphoblastic Leukemia Discrete Cosine Transform Watershed segmentation CAD system

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FaceMatch: Real-World Face image Retrieval 1st

FaceMatch: Real-World Face Image Retrieval

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

作者： Borovikov, Eugene Vajda, Szilard US Natl Lib Med 8600 Rockville Pike Bethesda MD 20894 USA

ISBN: (纸本)9789811048593;9789811048586

We researched and developed a practical methodology for face and image retrieval (FIR) based on optimally weighted image descriptor ensemble. We describe a single-image-per-person (SIPP) face image retrieval system for real-world applications that include large photo collection search, person location in disaster scenarios, semi-automatic image data annotation, etc. Our system provides efficient means for face detection, matching and annotation, working with unconstrained digital photos of variable quality, requiring no time-consuming training, yet showing a commercial performance level at its sub-tasks. Our system benefits public by providing practical FIR technology, annotated image data and web-services to a real-world family reunification system.

关键词： Face recognition image retrieval Family reunification

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Semi-supervised Text Categorization Using Recursive K-means Clustering 1st

Semi-supervised Text Categorization Using Recursive K-means ...

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

作者： Gowda, Harsha S. Suhil, Mahamad Guru, D. S. Raju, Lavanya Narayana Univ Mysore Dept Studies Comp Sci Mysore Karnataka India

ISBN: (纸本)9789811048593;9789811048586

In this paper, we present a semi-supervised learning algorithm for classification of text documents. A method of labeling unlabeled text documents is presented. The presented method is based on the principle of divide and conquer strategy. It uses recursive K-means algorithm for partitioning both labeled and unlabeled data collection. The K-means algorithm is applied recursively on each partition till a desired level partition is achieved such that each partition contains labeled documents of a single class. Once the desired clusters are obtained, the respective cluster centroids are considered as representatives of the clusters and the nearest neighbor rule is used for classifying an unknown text document. Series of experiments have been conducted to bring out the superiority of the proposed model over other recent state of the art models on 20Newsgroups dataset.

关键词： Unlabeled text documents Recursive K-means algorithm Semi-supervised learning Text categorization

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A Survey of Prospects and Problems in Hindustani Classical Raga Identification Using machine learning Techniques 1st

A Survey of Prospects and Problems in Hindustani Classical R...

引用

1st international conference on Intelligent Computing and Communication, (ICIC2)

作者： Banerjee, Sreeparna West Bengal Univ Technol Dept Nat Sci & Comp Sci & Engn Kolkata India

ISBN: (纸本)9789811020353;9789811020346

In this paper we present a survey of current research in Music Information Retrieval in North Indian Classical Music and describe all the characteristics of ragas used for classification. We then describe Bhatkhande's classification scheme and show how it can simplify the classification process of 100 ragas to 10 categories. We also discuss the issues that need to be addressed and the similarities and differences between Hindustani classical music and Western Classical music. Current research efforts on Raga identification are also described.

关键词： pattern recognition of raga Music information retrieval Audio descriptors Audio signal processing

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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 Workshop of machine learning under international conference on Document Analysis and recognition, ICDAR-WML 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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