Using features extracted

Xem 1-20 trên 101 kết quả Using features extracted
  • Building an accurate Named Entity Recognition (NER) system for languages with complex morphology is a challenging task. In this paper, we present research that explores the feature space using both gold and bootstrapped noisy features to build an improved highly accurate Arabic NER system.

    pdf5p hongdo_1 12-04-2013 44 4   Download

  • This paper proposes a simple and effective method to construct descriptive features for partially occluded face image recognition. This method is aimed for any small dataset which contains only one or two training images per subject, namely Locality oriented feature extraction for small training datasets (LOFESS).

    pdf11p vititan2711 13-08-2019 2 0   Download

  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Time-Frequency Feature Extraction of Newborn EEG Seizure Using SVD-Based Techniques

    pdf11p sting12 11-03-2012 40 4   Download

  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: RST-Resilient Video Watermarking Using Scene-Based Feature Extraction

    pdf19p sting12 11-03-2012 30 3   Download

  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Precession missile feature extraction using sparse component analysis of radar measurements

    pdf22p sting06 16-02-2012 26 2   Download

  • We investigate systems that identify opinion expressions and assigns polarities to the extracted expressions. In particular, we demonstrate the benefit of integrating opinion extraction and polarity classification into a joint model using features reflecting the global polarity structure. The model is trained using large-margin structured prediction methods.

    pdf6p hongdo_1 12-04-2013 35 2   Download

  • In this paper we present word sense disambiguation (WSD) experiments on ten highly polysemous verbs in Chinese, where significant performance improvements are achieved using rich linguistic features. Our system performs significantly better, and in some cases substantially better, than the baseline on all ten verbs. Our results also demonstrate that features extracted from the output of an automatic Chinese semantic role labeling system in general benefited the WSD system, even though the amount of improvement was not consistent across the verbs. ...

    pdf8p hongvang_1 16-04-2013 34 2   Download

  • This paper presents results from experiments in automatic classification of animacy for Norwegian nouns using decision-tree classifiers. The method makes use of relative frequency measures for linguistically motivated morphosyntactic features extracted from an automatically annotated corpus of Norwegian. The classifiers are evaluated using leave-oneout training and testing and the initial results are promising (approaching 90% accuracy) for high frequency nouns, however deteriorate gradually as lower frequency nouns are classified.

    pdf8p bunthai_1 06-05-2013 32 1   Download

  • We propose a content based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is evaluated on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show.

    pdf10p tieuthi3006 16-03-2018 13 1   Download

  • This paper presents a new approach of integrating Bottleneck feature (BNF) which is used for extracting tone information, to adapt to Multi Space Distribution Hidden Markov Model (MSDHMM) for Vietnamese Automatic Speech recognition (Vietnamese ASR).

    pdf8p doctorstrange1 15-06-2018 17 1   Download

  • This paper presents an automatic Heart Disease (HD) prediction method based on feature selection with data mining techniques using the provided symptoms and clinical information assigned in the patients dataset. Data mining which allows the extraction of hidden knowledges from the data and explores the relationship between attributes, is the promising technique for HD prediction.

    pdf15p thuyliebe 05-10-2018 23 0   Download

  • This article implements a face detection process as a preliminary step to monitor the state of drowsiness on vehicle's drivers. We propose an algorithm for pre-detection based on image processing and machine learning methods. A Gabor filter bank is used for facial features extraction.

    pdf4p cathydoll5 27-02-2019 9 0   Download

  • In shape feature extraction, the extracted feature vector is magnitude of five types edges (horizontal, vertical, 45, 135 degree and isotropic). Also Hough Transform is used to extract the edge features. Using different types of masks, the feature vector is obtained from the original image. Similarity measurement is performed by Euclidean Distance measure.

    pdf10p byphasse043256 24-03-2019 4 0   Download

  • The results showed that the best performance of the proposed application was through using k-means clustering and the pattern recognition neural network which merged with the K-means clustering using statistical extracted color features of image histogram with tiles size (16 × 16) pixels. The average time required to produce a mosaic photo with correcting colors was (26 seconds) and the mean of peak signal to noise ratio was (39.56594).

    pdf5p blossom162 31-03-2019 10 0   Download

  • This paper presents a human action recognition method using dynamic time warping and voting algorithms on 3D human skeletal models. In this method human actions, which are the combinations of multiple body part movements, are described by feature matrices concerning both spatial and temporal domains.

    pdf9p vixyliton2711 17-04-2019 4 0   Download

  • Classifying fingerprint images may require an important features extraction step. The scale-invariant feature transform which extracts local descriptors from images is robust to image scale, rotation and also to changes in illumination, noise, etc. It allows to represent an image in term of the comfortable bag-of-visual-words.

    pdf10p vititan2711 13-08-2019 7 0   Download

  • A fundamental approach in signal processing is to design a statistical generative model of the observed signals. The components in the generative model then give a representation of the data. Such a representation can then be used in such tasks as compression, denoising, and pattern recognition. This approach is also useful from a neuroscientific viewpoint, for modeling the properties of neurons in primary sensory areas. In this chapter, we consider a certain class of widely used signals, which we call natural images....

    pdf17p duongph05 09-06-2010 74 12   Download

  • This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene. The features are invariant to image scale and rotation, and are shown to provide robust matching across a a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images.

    pdf28p friends 20-06-2010 86 10   Download

  • Supercritical Fluid Extraction Technology in Food Processing provide some necessary content to help you have more materials for reference as well as practice knowledge. Hope the document gives you good lessons for you to study.

    pdf15p conduongdinhmenh 07-05-2013 40 5   Download

  • We learn a joint model of sentence extraction and compression for multi-document summarization. Our model scores candidate summaries according to a combined linear model whose features factor over (1) the n-gram types in the summary and (2) the compressions used. We train the model using a marginbased objective whose loss captures end summary quality. Because of the exponentially large set of candidate summaries, we use a cutting-plane algorithm to incrementally detect and add active constraints efficiently. ...

    pdf10p hongdo_1 12-04-2013 38 3   Download



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