130 citations · 315 across the 15 of their papers we have counts for
15 papers
Discovering Dynamic Effective Connectome of Brain with Bayesian Dynamic DAG Learning
Abdolmahdi Bagheri, Mohammad Pasande, Kevin Bello +2
Understanding the complex mechanisms of the brain can be unraveled by extracting the Dynamic Effective Connectome (DEC). Recently, score-based Directed Acyclic Graph (DAG) discover…
A Tractable Truthful Profit Maximization Mechanism Design with Autonomous Agents
Mina Montazeri, Hamed Kebriaei, Babak N. Araabi
Task allocation is a crucial process in modern systems, but it is often challenged by incomplete information about the utilities of participating agents. In this paper, we propose…
Brain Effective Connectome based on fMRI and DTI Data: Bayesian Causal Learning and Assessment
Abdolmahdi Bagheri, Mahdi Dehshiri, Yamin Bagheri +2
Neuroscientific studies aim to find an accurate and reliable brain Effective Connectome (EC). Although current EC discovery methods have contributed to our understanding of brain o…
Stochastic First-Order Learning for Large-Scale Flexibly Tied Gaussian Mixture Model
Mohammad Pasande, Reshad Hosseini, Babak Nadjar Araabi
Gaussian Mixture Models (GMMs) are one of the most potent parametric density models used extensively in many applications. Flexibly-tied factorization of the covariance matrices in…
-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells
Sajad Movahedi, Melika Adabinejad, Ayyoob Imani +4
Differentiable neural architecture search (DARTS) is a popular method for neural architecture search (NAS), which performs cell-search and utilizes continuous relaxation to improve…
Contour Integration using Graph-Cut and Non-Classical Receptive Field
Zahra Mousavi Kouzehkanan, Reshad Hosseini, Babak Nadjar Araabi
Many edge and contour detection algorithms give a soft-value as an output and the final binary map is commonly obtained by applying an optimal threshold. In this paper, we propose…
Attention-based Assisted Excitation for Salient Object Detection
Saeed Masoudnia, Melika Kheirieh, Abdol-Hossein Vahabie +1
Visual attention brings significant progress for Convolution Neural Networks (CNNs) in various applications. In this paper, object-based attention in human visual cortex inspires u…
Assisted Excitation of Activations: A Learning Technique to Improve Object Detectors
Mohammad Mahdi Derakhshani, Saeed Masoudnia, Amir Hossein Shaker +4
We present a simple and effective learning technique that significantly improves mAP of YOLO object detectors without compromising their speed. During network training, we carefull…
Evaluation of Dataflow through layers of Deep Neural Networks in Classification and Regression Problems
Ahmad Kalhor, Mohsen Saffar, Melika Kheirieh +2
This paper introduces two straightforward, effective indices to evaluate the input data and the data flowing through layers of a feedforward deep neural network. For classification…
Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs
Saeed Masoudnia, Omid Mersa, Babak N. Araabi +3
Offline Signature Verification (OSV) is a challenging pattern recognition task, especially in presence of skilled forgeries that are not available during training. This study aims…
Active Transfer Learning for Persian Offline Signature Verification
Taraneh Younesian, Saeed Masoudnia, Reshad Hosseini +1
Offline Signature Verification (OSV) remains a challenging pattern recognition task, especially in the presence of skilled forgeries that are not available during the training. Thi…
Learning Representations from Persian Handwriting for Offline Signature Verification, a Deep Transfer Learning Approach
Omid Mersa, Farhood Etaati, Saeed Masoudnia +1
Offline Signature Verification (OSV) is a challenging pattern recognition task, especially when it is expected to generalize well on the skilled forgeries that are not available du…
Incremental learning of high-level concepts by imitation
Mina Alibeigi, Majid Nili Ahmadabadi, Babak Nadjar Araabi
Nowadays, robots become a companion in everyday life. To be well-accepted by humans, robots should efficiently understand meanings of their partners' motions and body language, and…
UTSig: A Persian Offline Signature Dataset
Amir Soleimani, Kazim Fouladi, Babak N. Araabi
The pivotal role of datasets in signature verification systems motivates researchers to collect signature samples. Distinct characteristics of Persian signature demands for richer…
Pigment Melanin: Pattern for Iris Recognition
Mahdi S. Hosseini, Babak N. Araabi, Hamid Soltanian-Zadeh
Recognition of iris based on Visible Light (VL) imaging is a difficult problem because of the light reflection from the cornea. Nonetheless, pigment melanin provides a rich feature…