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20122024
most citedSpectral Unmixing of Hyperspectral Imagery using Multilayer NMF

166 citations · 223 across the 11 of their papers we have counts for

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10 papers · 1 filter

cs.CV20241 cited

Diagnosis of Skin Cancer Using VGG16 and VGG19 Based Transfer Learning Models

Amir Faghihi, Mohammadreza Fathollahi, Roozbeh Rajabi

Today, skin cancer is considered as one of the most dangerous and common cancers in the world which demands special attention. Skin cancer may be developed in different types; incl…

cs.CV2022

Deep Learning Based Framework for Iranian License Plate Detection and Recognition

Mojtaba Shahidi Zandi, Roozbeh Rajabi

License plate recognition systems have a very important role in many applications such as toll management, parking control, and traffic management. In this paper, a framework of de…

cs.CV202154 cited

Drone Detection Using Convolutional Neural Networks

Fatemeh Mahdavi, Roozbeh Rajabi

In image processing, it is essential to detect and track air targets, especially UAVs. In this paper, we detect the flying drone using a fisheye camera. In the field of diagnosis a…

cs.CV2019

Clustered Multitask Nonnegative Matrix Factorization for Spectral Unmixing of Hyperspectral Data

Sara Khoshsokhan, Roozbeh Rajabi, Hadi Zayyani

In this paper, the new algorithm based on clustered multitask network is proposed to solve spectral unmixing problem in hyperspectral imagery. In the proposed algorithm, the cluste…

cs.CV2019

Sparsity Constrained Distributed Unmixing of Hyperspectral Data

Sara Khoshsokhan, Roozbeh Rajabi, Hadi Zayyani

Spectral unmixing (SU) is a technique to characterize mixed pixels in hyperspectral images measured by remote sensors. Most of the spectral unmixing algorithms are developed using…

cs.CV2018

Hyperspectral Unmixing Based on Clustered Multitask Networks

Sara Khoshsokhan, Roozbeh Rajabi, Hadi Zayyani

Hyperspectral remote sensing is a prominent research topic in data processing. Most of the spectral unmixing algorithms are developed by adopting the linear mixing models. Nonnegat…