BACKGROUND: Textual corpora are extremely important for various NLP applications as they provide information necessary for creating, setting and testing those applications and the corresponding tools. They are also crucial for designing reliable meth...
Neural networks : the official journal of the International Neural Network Society
Aug 5, 2020
Many tasks involve learning representations from matrices, and Non-negative Matrix Factorization (NMF) has been widely used due to its excellent interpretability. Through factorization, sample vectors are reconstructed as additive combinations of lat...
Measuring the semantic similarity between words is important for natural language processing tasks. The traditional models of semantic similarity perform well in most cases, but when dealing with words that involve geographical context, spatial seman...
Users of social media often share their feelings or emotional states through their posts. In this study, we developed a deep learning model to identify a user's mental state based on his/her posting information. To this end, we collected posts from m...
This study developed a medicine query system based on Semantic Web and open data especially for self-medication users to search over-the-counter (OTC) medicines. Most existing medicine query systems are based on keyword searches. If users are uncerta...
Computational intelligence and neuroscience
Jul 11, 2020
Cross-modal search has become a research hotspot in the recent years. In contrast to traditional cross-modal search, social network cross-modal information search is restricted by data quality for arbitrary text and low-resolution visual features. In...
BACKGROUND: Biomedical ontologies have been growing quickly and proven to be useful in many biomedical applications. Important applications of those data include estimating the functional similarity between ontology terms and between annotated biomed...
BACKGROUND: For the segmentation of medical imaging data, a multitude of precise but very specific algorithms exist. In previous studies, we investigated the possibility of segmenting MRI data to determine cerebrospinal fluid and brain volume using a...
In this paper, we present an evaluation of four encoder-decoder CNNs in the segmentation of the prostate gland in T2W magnetic resonance imaging (MRI) image. The four selected CNNs are FCN, SegNet, U-Net, and DeepLabV3+, which was originally proposed...
Neural networks : the official journal of the International Neural Network Society
Jun 2, 2020
Image style transfer renders the content of an image into different styles. Current methods made decent progress with transferring the style of single image, however, visual statistics from one image cannot reflect the full scope of an artist. Also, ...