Deep Learning

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

Bayesian Deep Learning | Uncertainty in Deep Learning

Infant Head Circumference Measurement Using Deep Learning Techniques

Infant's head circumference measurement and and its growth monitoring plays a crucial role in diagnosis the diseases which cause a deformation in the infant's head. Due to the fact that the contact measurement, which is performed using a tape measure and a caliper, has problems such as transmitting disease, infecting, not comfortable and disruption relaxing the baby, going to non-contact measur...

Corefrence resolution with deep learning in the Persian Labnguage

Coreference resolution is an advanced issue in natural language processing. Nowadays, due to the extension of social networks, TV channels, news agencies, the Internet, etc. in human life, reading all the contents, analyzing them, and finding a relation between them require time and cost. In the present era, text analysis is performed using various natural language processing techniques, one ...

Named Entity Recognition in Persian Text using Deep Learning

Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...