no code implementations • 8 Aug 2023 • Dorsa Rahmatian, Monireh Moshavash, Mahdi Eftekhari, Kamran Hoseinkhani
The first stage of producing a carpet is to prepare its map, which is a difficult, time-consuming, and expensive task.
no code implementations • 1 Aug 2023 • Mohammadreza Shakouri, Fatemeh Iranmanesh, Mahdi Eftekhari
The limited availability of labeled chest X-ray datasets is a significant bottleneck in the development of medical imaging methods.
no code implementations • 22 Jun 2023 • Farshad Saberi-Movahed, Mohammad K. Ebrahimpour, Farid Saberi-Movahed, Monireh Moshavash, Dorsa Rahmatian, Mahvash Mohazzebi, Mahdi Shariatzadeh, Mahdi Eftekhari
Deep Metric Learning (DML) models rely on strong representations and similarity-based measures with specific loss functions.
1 code implementation • 28 Mar 2023 • Hojjat Mokhtarabadi, Kave Bahraman, Mehrdad Hosseinzadeh, Mahdi Eftekhari
Empirical evaluations on correlation-based metrics, such as Kendall's $\tau$ and Spearman's $\rho$ demonstrate the superiority of our approach compared to existing state-of-the-art methods in assigning relative scores to the input frames.
1 code implementation • IJMLC 2020 • Ali Hassani, Amir Iranmanesh, Mahdi Eftekhari, Abbas Salemi
One of the applications of center-based clustering algorithms such as K-Means is partitioning data points into K clusters.
no code implementations • 18 Sep 2019 • Nader Asadi, Amir M. Sarfi, Mehrdad Hosseinzadeh, Zahra Karimpour, Mahdi Eftekhari
In this work, we propose a learning framework to improve the shape bias property of self-supervised methods.
Ranked #58 on Domain Generalization on PACS
no code implementations • 1 Jul 2019 • Nader Asadi, AmirMohammad Sarfi, Mehrdad Hosseinzadeh, Sahba Tahsini, Mahdi Eftekhari
Our method can be applied to any layer of any arbitrary model without the need of any modification or additional training.
no code implementations • 31 Jul 2018 • Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn
This paper presents a new feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset.