Content-based image retrieval (CBIR) is the task of finding images in a database that are most similar to input query based on its visual characteristics. Several methods from state art (bag words, VLAD, etc.) or recent deep leaning try solve CBIR problem. In particular, learning new field and used for several vision applications including CBIR. But, even with increase performance algorithms, t...

Mapping and merging of multiple ontologies to produce consistent, coherent and correct merged global ontology is an essential process to enable heterogeneous multi-vendors semantic-based systems to communicate with each other. To generate such a global ontology automatically, the individual ontologies must be free of (all types of) errors. We have observed that the present error classification ...

We propose a method for semantic structure analysis of noun phrases using Abstract Meaning Representation (AMR). AMR is a graph representation for the meaning of a sentence, in which noun phrases (NPs) are manually annotated with internal structure and semantic relations. We extract NPs from the AMR corpus and construct a data set of NP semantic structures. We also propose a transition-based al...

Background: Hyaline cartilage defects exhibit a major challenge in the field of orthopedic surgery owing to its limited repair capacity. On the other hand, mesenchymal stem cells (MSCs) are regarded as potent cells with a property of cartilage regeneration. We aimed to optimize marrow-derived MSC chondrogenic culture using a small bioactive molecule referred to as BIO. Methods: MSCs from the ma...

This paper pursues obtaining Jacobi spectral collocation methods to solve Caputo fractional differential equations numerically. We used the shifted Jacobi–Gauss–Lobatto or Jacobi–Gauss–Radau quadrature nodes as points and derived differentiation matrices for derivatives. With matrices, were transformed into linear systems, which are easier solve. Two types of numerical simulations, results demo...

Semantic Segmentation is the process of assigning a label to every pixel in image that share same semantic properties and stays challenging task computer vision. In recent years, due large availability training data performance segmentation has been greatly improved by using deep learning techniques. A number novel methods have proposed. However, some crucial fields we can't assure sufficient l...

Location prediction has attracted much attention due to its important role in many location-based services, such as food delivery, taxi-service, real-time bus system, and advertisement posting. Traditional prediction methods often cluster track points into regions and mine movement patterns within the regions. Such methods lose information of points along the road and cannot meet the demand of ...

E-mail: [email protected] Abstract: Several hashing-based methods for Approximate Nearest Neighbors (ANN) search in a large data set have been proposed recently. In particular, semi-supervised hashing utilizes semantic similarity given for a small fraction of pairwise data samples and active hashing aims to improve the performance for ANN search by relying on an expert for the labeling of the...

According to many theories, semantic representations reflect the parallel activation of information coded across a distributed set of modality-specific association brain cortices. This view is challenged by the neurodegenerative condition known as semantic dementia (SD), in which relatively circumscribed, bilateral atrophy of the anterior temporal lobes results in selective degradation of core ...