activity
20162021
most citedClassification of Time-Series Images Using Deep Convolutional Neural Networks

89 citations · 101 across the 2 of their papers we have counts for

collaborators

5 papers

eess.IV202112 cited

Deep Multi-Resolution Dictionary Learning for Histopathology Image Analysis

Nima Hatami, Mohsin Bilal, Nasir Rajpoot

The problem of recognizing various types of tissues present in multi-gigapixel histology images is an important fundamental pre-requisite for downstream analysis of the tumor micro…

cs.CV2018

Magnetic Resonance Spectroscopy Quantification using Deep Learning

Nima Hatami, Michaël Sdika, Hélène Ratiney

Magnetic resonance spectroscopy (MRS) is an important technique in biomedical research and it has the unique capability to give a non-invasive access to the biochemical content (me…

cs.CV2018

Bag of Recurrence Patterns Representation for Time-Series Classification

Nima Hatami, Yann Gavet, Johan Debayle

Time-Series Classification (TSC) has attracted a lot of attention in pattern recognition, because wide range of applications from different domains such as finance and health infor…

cs.CV201789 cited

Classification of Time-Series Images Using Deep Convolutional Neural Networks

Nima Hatami, Yann Gavet, Johan Debayle

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the…

cs.CV2016

Automatic Identification of Retinal Arteries and Veins in Fundus Images using Local Binary Patterns

Nima Hatami, Michael Goldbaum

Artery and vein (AV) classification of retinal images is a key to necessary tasks, such as automated measurement of arteriolar-to-venular diameter ratio (AVR). This paper comprehen…