activity
20142023
most citedRLAS-BIABC: A Reinforcement Learning-Based Answer Selection Using the BERT Model Boosted by an Improved ABC Algorithm

36 citations · 41 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20234 cited

Machine Learning Techniques for Predicting the Short-Term Outcome of Resective Surgery in Lesional-Drug Resistance Epilepsy

Zahra Jourahmad, Jafar Mehvari Habibabadi, Houshang Moein +4

In this study, we developed and tested machine learning models to predict epilepsy surgical outcome using noninvasive clinical and demographic data from patients. Methods: Seven di…

cs.CL202336 cited

RLAS-BIABC: A Reinforcement Learning-Based Answer Selection Using the BERT Model Boosted by an Improved ABC Algorithm

Hamid Gharagozlou, Javad Mohammadzadeh, Azam Bastanfard +1

Answer selection (AS) is a critical subtask of the open-domain question answering (QA) problem. The present paper proposes a method called RLAS-BIABC for AS, which is established o…

cs.CV20221 cited

Semi-supervised Vector-Quantization in Visual SLAM using HGCN

Amir Zarringhalam, Saeed Shiry Ghidary, Ali Mohades Khorasani

In this paper, two semi-supervised appearance based loop closure detection technique, HGCN-FABMAP and HGCN-BoW are introduced. Furthermore an extension to the current state of the…

cs.RO2022

Self-supervised Vector-Quantization in Visual SLAM using Deep Convolutional Autoencoders

Amir Zarringhalam, Saeed Shiry Ghidary, Ali Mohades Khorasani

In this paper, we introduce AE-FABMAP, a new self-supervised bag of words-based SLAM method. We also present AE-ORB-SLAM, a modified version of the current state of the art BoW-bas…

cs.RO2014

A Framework for learning multi-agent dynamic formation strategy in real-time applications

Mehrab Norouzitallab, Valiallah Monajjemi, Saeed Shiry Ghidary +1

Formation strategy is one of the most important parts of many multi-agent systems with many applications in real world problems. In this paper, a framework for learning this task i…