M
Mandana Hamidi
Researcher at Istituto Italiano di Tecnologia
Publications - 10
Citations - 223
Mandana Hamidi is an academic researcher from Istituto Italiano di Tecnologia. The author has contributed to research in topics: Fuzzy classification & Fuzzy set operations. The author has an hindex of 7, co-authored 10 publications receiving 217 citations. Previous affiliations of Mandana Hamidi include Islamic Azad University.
Papers
More filters
Journal ArticleDOI
Online learning of task-driven object-based visual attention control
TL;DR: A biologically-motivated computational model for learning task-driven and object-based visual attention control in interactive environments and is evaluated on visual navigation tasks, where obtained results lend support to the applicability and usefulness of the developed method for robotics.
Journal ArticleDOI
Robust Handwritten Character Recognition with Features Inspired by Visual Ventral Stream
TL;DR: This paper focuses on the applicability of the features inspired by the visual ventral stream for handwritten character recognition, and an analysis is conducted to evaluate the robustness of this approach to orientation, scale and translation distortions.
Journal ArticleDOI
Support Vector Machine for Persian Font Recognition
Ali Borji,Mandana Hamidi +1 more
TL;DR: This paper examines the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images and considers document images as textures and uses Gabor filter responses for identifying the fonts.
Journal ArticleDOI
Invariance analysis of modified C2 features: case study—handwritten digit recognition
Mandana Hamidi,Ali Borji +1 more
TL;DR: This study shows that using features proposed by the modified model results in higher handwritten digit recognition rates compared with the original model over English and Farsi handwritten digit datasets, and demonstrates higher invariance of the modified models to various image distortions.
Journal Article
Evolving a Fuzzy Rule-Base for Image Segmentation
Ali Borji,Mandana Hamidi +1 more
TL;DR: The aim here is to automatically produce a fuzzy system for color classification and image segmentation with least number of rules and minimum error rate and less computational load when using this method compared with other methods, because it generates a smaller number of fuzzy rules.