bag-of-features representation
Map reduce based bag of phrases representation and distributional features incorporation for text classification
... Document representation is the process of converting raw documents into a set of features that shall be fed into machine learning ...algorithms. Features for applying machine learning algorithms to ...
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Video Scene Detection by Multimodal Bag of Features
... video representation using scene transition ...visual features, which are domain-independent, the authors agree that using semantics could enhance their ...
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Bag of Features Based Remote Sensing Image Classification Using RANSAC And SVM
... BOF representation, experimenting with more sophisticated classifiers. Bag-of -Words is combined with texton-based classifier for differentiating anaplastic and non-anaplastic medulloblastoma on digitized ...
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CBIR Framework based on Bag-of-Features (BoF) and Super Vector Coding (SVC)
... To link feature extraction and feature pooling [24, 25], core component of image classification is used i.e. feature coding that significantly impacts image classification in terms of both accuracy and speed. In proposed ...
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Distributional Features for Text Categorization Based on Weight
... “bag-of-word” representation, previous researches usually assign a word with values that express whether this word appears in the document concerned or how frequently this word ...distributional ...
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Aggregating Continuous Word Embeddings for Information Retrieval
... a Bag-of-Embedded-Words ...a bag-of-features (BoF) where each real-valued feature describes local proper- ties of the image (such as its color, texture or ...fixed-length representation which ...
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Extracting Social Power Relationships from Natural Language
... additional representation. Grouping features by length was a simple but arbi- trary method for reducing dimensionality, yet sometimes produced small bins of otherwise good ...those features with a ...
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Detecting Depression in Social Media using Fine Grained Emotions
... a representation based on the occurrences of broad emotions and the words that do not have an associated ...approach Bag-of-Emotions (BoE). We also compared our results against a Bag-of-Words ...
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One-shot Learning Gesture Recognition from RGB-D Data Using Bag of Features
... distinctive features and how to learn a discriminative model from only one training sample per gesture ...feature representation called 3D enhanced motion scale-invariant feature transform (3D EMoSIFT) is ...
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A Bag of Features Based Approach for Classification of Motile Sperm Cells
... 2) Bag-of-Features (BoF): Processing large SURF vectors can represent a high computational cost. Hence, the BoF model is employed to reduce the feature representation of the images. The aim of BoF is ...
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More than Bag-of-Words: Sentence-based Document Representation for Sentiment Analysis
... In this work we propose a solution to the afore- mentioned problem by building a meta-classifier which models each document as a sequence of emotionally annotated sentences. The advantage of this modeling is that it ...
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Performance Evaluation and Study of Bag of Visual Words and Cascade Classifiers in Object Recognition
... The Bag of features or Bag of words is a well-known classification method for object ...created. Bag of Words is a representation based on visual ...extracted features from the ...
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Development of Bag-1L as a therapeutic target in androgen receptor-dependent prostate cancer.
... by Bag-1 status at HSPC using Fisher’s exact test for categorical characteristics, the Chi-squared test for trend for ordinal characteristics and either an unpaired t-test for continuous data, if normally ...
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Combining Probability Based Rankers for Action Item Detection
... Our corpus consists of e-mails obtained from vol- unteers at an educational institution and covers subjects such as: organizing a research work- shop, arranging for job-candidate interviews, pub- lishing proceedings, and ...
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Artistic Content Representation and Modelling based on Visual Style Features
... Li, X. et al. [107] present a comprehensive method for decomposition of complex shapes into Geons, thereby developing a structural representation of the context. This is ideal for the proposed algorithm, and the ...
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Task-Driven Linguistic Analysis based on an Underspecified Features Representation
... We explored the possibility of a task-driven approach to text understanding, where the process is guided by the ap- plication for which it is needed. We believe this to be an advantageous alternative to current NLP ...
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Bag
... In algebraic coding theory, one of the main goals is to produce good error-correcting linear codes by means of larger minimum distance and code rate.. Towards this, the cyclic code is on[r] ...
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A Survey on Hate Speech Detection using Natural Language Processing
... linguistic features tailored to the task of hate speech ...tactic features include the detection of imperative statements ...semantic features to pre- vent false ...
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Multimodal Differential Network for Visual Question Generation
... the Representation module to find the embeddings for the image and ground truth caption without using the supporting and contrast- ing ...joint representation of the target image and ground truth ...joint ...
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Identification of Duplication in Questions Posed on Knowledge Sharing Platform Quora using Machine Learning Techniques
... The second case was to extract the features using TFIDF-Vectorizer. After that the ML techniques were applied for modeling and the results were tabulated (see Table.3). For Logistic Regression, it gave an accuracy ...
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