نتایج جستجو برای: bag of visual word
تعداد نتایج: 21204809 فیلتر نتایج به سال:
abstract compound is a word-formation process that are made two free morpheme (independent) and forms a new word with a new meaning that consists of meaning of both two component of compound. avestan language is one of the ancient iranian languages that is one of the indo-iranian languages. indo-iranian languages is one branch of indo-european languages. structure of compound noun and adjectiv...
the changes in todays world organization, to the extent that instability can be characterized with the most stable organizations called this afternoon. if you ever change management component, an additional value to the organization was considered, today, these elements become the foundation the organization is survival. the definition of the entrepreneur to identify opportunities to exploit a...
Vocabulary generation is the essential step in the bag-ofwords image representation for visual concept recognition, because its quality affects classification performance substantially. In this paper, we propose a hybrid method for visual word generation which combines unsupervised density-based clustering with the discriminative power of fast support vector machines. We aim at three goals: bre...
different researchers in different parts of the world have investigated the strategies used to translate written works ranging from novels to classroom assignments. however, by the significant increase in the number of postgraduate students in iran in the last few years, a very common kind of translation in iran includes translating abstracts of master’s theses. in this work, the researcher hav...
It is a challenging and important task to retrieve images from a large and highly varied image data set based on their visual contents. Problems like how to fill the semantic gap between image features and the user have attracted a lot of attention from the research community. Recently, the 'bag of visual words' approach exhibits very good performance in content-based image retrieval (CBIR). Ho...
Scene classification based on local keypoint features has emerged as a promising research direction. Each image is represented by a “bag of visual words” as high-dimensional, vector-quantized keypoint features, which is analogous to the “bag of words” representation of text documents. Based on such representation, we take a fully text categorization approach to the scene classification problem,...
the present dissertation aims to investigate four-word lexical bundles in applied linguistics research articles by iranian and internationally-published writers. the aims of this study are two-fold: first of all, attempts have been made to create a comprehensive list of the most commonly used four-word lexical bundles categorized by their type and token frequency, their structural characteristi...
In this paper, we propose a novel approach for text classification based on clustering word embeddings, inspired by the bag of visual words model, which is widely used in computer vision. After each word in a collection of documents is represented as word vector using a pre-trained word embeddings model, a k-means algorithm is applied on the word vectors in order to obtain a fixed-size set of c...
Focusing on the problem of natural image categorization, a novel multi-instance learning (MIL) algorithm based on rough set (RS) attribute reduction and support vector machine (SVM) is proposed. This algorithm regards each image as a bag, and lowlevel visual features of the segmented regions as instances. Firstly, a collection of "visual-words" is generated by Gaussian mixture model (GMM) clust...
This paper presents a direct semantic analysis method for learning the correlation matrix between visual and textual words from socially tagged images. In the literature, to improve the traditional visual bag-of-words (BOW) representation, latent semantic analysis has been studied extensively for learning a compact visual representation, where each visual word may be related to multiple latent ...
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