8 citations · 21 across the 9 of their papers we have counts for
11 papers
CFGPNet: Cross-Attention-Based Fused Gradient Programmed Network Framework for Multispectral Object Detection
Nima Hatami, Karim Faez, Saeed Sharifian +1
Multispectral object detection combines visible and thermal imagery to improve perception under challenging illumination and environmental conditions. However, differences in modal…
Enhanced Depth Estimation and 3D Geometry Reconstruction using Bayesian Helmholtz Stereopsis with Belief Propagation
Razieh Azizi, Hamidreza Amindavar, Hassan Aghaeinia
Helmholtz stereopsis is one the versatile techniques for 3D geometry reconstruction from 2D images of objects with unknown and arbitrary reflectance surfaces. HS eliminates the nee…
Swin-Tempo: Temporal-Aware Lung Nodule Detection in CT Scans as Video Sequences Using Swin Transformer-Enhanced UNet
Hossein Jafari, Karim Faez, Hamidreza Amindavar
Lung cancer is highly lethal, emphasizing the critical need for early detection. However, identifying lung nodules poses significant challenges for radiologists, who rely heavily o…
Stellar Karaoke: deep blind separation of terrestrial atmospheric effects out of stellar spectra by velocity whitening
Nima Sedaghat, Brianna M. Smart, J. Bryce Kalmbach +2
We report a study exploring how the use of deep neural networks with astronomical Big Data may help us find and uncover new insights into underlying phenomena: through our experime…
Deep Bayesian Active Learning, A Brief Survey on Recent Advances
Salman Mohamadi, Hamidreza Amindavar
Active learning frameworks offer efficient data annotation without remarkable accuracy degradation. In other words, active learning starts training the model with a small size of l…
A New Framework For Spatial Modeling And Synthesis of Genome Sequence
Salman Mohamadi, Farhang Yeganegi, Hamidreza Amindavar
This paper provides a framework in order to statistically model sequences from human genome, which is allowing a formulation to synthesize gene sequences. We start by converting th…
Graph-Based Method for Anomaly Prediction in Brain Network
Jalal Mirakhorli, Hamidreza Amindavar, Mojgan Mirakhorli
Resting-state functional MRI (rs-fMRI) in functional neuroimaging techniques have improved in brain disorders, dysfunction studies via mapping the topology of the brain connections…
A Novel Maneuvering Target Tracking Approach by Stochastic Volatility GARCH Model
Ehsan Hajiramezanali, Seyyed Hamed Fouladi, Hamidreza Amindavar
In this paper, we introduce a new single model maneuvering target tracking approach using stochastic differential equation (SDE) based on GARCH volatility. The traditional input es…
Semi-Supervised Hierarchical Semantic Object Parsing
Jalal Mirakhorli, Hamidreza Amindavar
Models based on Convolutional Neural Networks (CNNs) have been proven very successful for semantic segmentation and object parsing that yield hierarchies of features. Our key insig…
Sparse Estimation with Generalized Beta Mixture and the Horseshoe Prior
Zahra Sabetsarvestani, Hamidreza Amindavar
In this paper, the use of the Generalized Beta Mixture (GBM) and Horseshoe distributions as priors in the Bayesian Compressive Sensing framework is proposed. The distributions are…
A Hybrid Global Minimization Scheme for Accurate Source Localization in Sensor Networks
Hamidreza Aghasi, Hamidreza Amindavar, Alireza Aghasi
We consider the localization problem of multiple wideband sources in a multi-path environment by coherently taking into account the attenuation characteristics and the time delays…