International Symposium on Telecommunication (IST)

Home / 11th International Symposium on Telecommunication (IST'2024)

Local Graph Convolutional Network for Hyperspectral Target Detection

Authors :

Maryam Imani¹

1- Tarbiat Modares University

Keywords :

graph convolutional network،hyperspectral target detection،deep learning

Abstract :

A graph convolutional network (GCD) is suggested for hyperspectral target detection in this paper. To extract the spatial neighborhood information in each local region of the hyperspectral image, extract latent spectral relationships among neighbors and explore the irregular class boundaries corresponding to each local patch centered at the pixel under test, a small local graph is constructed for each pixel. After several graph convolutional blocks for exploration of spectral-spatial latent dependencies, the label of each pixel is predicted in the last layer. The GCD with composing a local graph correspond to each pixel and its spatial neighbors can well enhance discrimination among target and background, which leads to significant improvement in the detection results. The experimental results show superiority of GCN compared to convolutional neural network (CNN) and several other hyperspectral target detectors.

Papers List

List of archived papers

A Review of Feature Selection Methods for Disease Risk Prediction and healhcare

Fatemeh Mohammadi

Design and Implementation of a High-Efficiency 5W Ku-Band Power Amplifier Using a Bare Die GaN HEMT for Satellite Uplink Applications

Ehsan Rafiei - Amin Azimi - Vahid Nayyeri - Roghieh Karimzadeh Baee

A Low-Cost Passive Thermal IR Imaging System for Automated Hidden Object Detection Using AI

Mohammad Javad Amiri - Saman Ghazanfari - Mohammad Parsa Mirzaei Sarmad - Mohammad Fakharzadeh

Key Performance Indicators in Information Sharing and Analysis Centers (ISAC)

Fatemeh Valinezhad - Afsaneh Madani

Analytical Performance model for Sliced 5G core network

Touraj Shabanian Boroujeni - Amin Ghalami Osgouei

MIMO Transceiver with Ultra-Power-Efficient Analog-Based Processing Toward Tbps Wireless Communication

Mir Mahdi Safari - Jafar Pourrostam - Seyed Hosein Mousavi

SegLoc: Visual Self-supervised Learning Scheme for Dense Prediction Tasks on X-ray Images

Shervin Halat - Mohammad Rahmati - Ehsan Nazerfard

FL-ProtectX: Combating Label flipping in complex multi-agent environments

Mohammad Ali Zamani - Fatemeh Amiri - Pooya Jamshidi - Seyed Mahdi Hosseini - Nasser Yazdani

Optimizing Smart Parking Solutions in Vehicle-to-Vehicle Networks

Alireza Yari - Pouya Fathollahzadeh

Examining the legal challenges and loopholes of artificial intelligence by considering the upstream documents of the country

Mohammad Hadi Bokaei - Elham Rafati - Davood Heidari Kani - Farbod Rabizadeh Fard - Ali Derakhshani - Iman Derakhshani - Nooshin Bodaghi - Reza Baderestani - Neda Nedaei