Pedram Ghamisi

research

∙ 05/17/2023

Tinto: Multisensor Benchmark for 3D Hyperspectral Point Cloud Segmentation in the Geosciences

The increasing use of deep learning techniques has reduced interpretatio...

0 Ahmed J. Afifi, et al. ∙

research

∙ 04/03/2023

Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks

Change detection, as an important application for high-resolution remote...

0 Shizhen Chang, et al. ∙

research

∙ 04/03/2023

Changes to Captions: An Attentive Network for Remote Sensing Change Captioning

In recent years, advanced research has focused on the direct learning an...

0 Shizhen Chang, et al. ∙

research

∙ 12/19/2022

AI Security for Geoscience and Remote Sensing: Challenges and Future Trends

Recent advances in artificial intelligence (AI) have significantly inten...

0 Yonghao Xu, et al. ∙

research

∙ 11/15/2022

Backdoor Attacks for Remote Sensing Data with Wavelet Transform

Recent years have witnessed the great success of deep learning algorithm...

0 Nikolaus Dräger, et al. ∙

research

∙ 10/09/2022

Sketched Multi-view Subspace Learning for Hyperspectral Anomalous Change Detection

In recent years, multi-view subspace learning has been garnering increas...

0 Shizhen Chang, et al. ∙

research

∙ 09/28/2022

Hyperspectral Remote Sensing Benchmark Database for Oil Spill Detection with an Isolation Forest-Guided Unsupervised Detector

Oil spill detection has attracted increasing attention in recent years s...

23 Puhong Duan, et al. ∙

research

∙ 09/26/2022

EOD: The IEEE GRSS Earth Observation Database

In the era of deep learning, annotated datasets have become a crucial as...

0 Michael Schmitt, et al. ∙

research

∙ 08/24/2022

Learning crop type mapping from regional label proportions in large-scale SAR and optical imagery

The application of deep learning algorithms to Earth observation (EO) in...

7 Laura E. C. La Rosa, et al. ∙

research

∙ 08/08/2022

Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield Networks

The synthesis of high-resolution remote sensing images based on text des...

3 Yonghao Xu, et al. ∙

research

∙ 04/18/2022

Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives

In recent years, supervised learning has been widely used in various tas...

4 Jun Yue, et al. ∙

research

∙ 04/14/2022

HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising Package

As with any physical instrument, hyperspectral cameras induce different ...

0 Daniel Coquelin, et al. ∙

research

∙ 03/18/2022

Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection

Recently, many collaborative representation-based (CR) algorithms have b...

0 Shizhen Chang, et al. ∙

research

∙ 02/14/2022

Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark

Deep neural networks have achieved great success in many important remot...

9 Yonghao Xu, et al. ∙

research

∙ 02/08/2022

Consistency-Regularized Region-Growing Network for Semantic Segmentation of Urban Scenes with Point-Level Annotations

Deep learning algorithms have obtained great success in semantic segment...

0 Yonghao Xu, et al. ∙

research

∙ 01/15/2022

Asymmetric Hash Code Learning for Remote Sensing Image Retrieval

Remote sensing image retrieval (RSIR), aiming at searching for a set of ...

8 Weiwei Song, et al. ∙

research

∙ 01/10/2022

NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery

The use of deep learning for water extraction requires precise pixel-lev...

7 Ming Lu, et al. ∙

research

∙ 12/21/2021

Deep Learning and Earth Observation to Support the Sustainable Development Goals

The synergistic combination of deep learning models and Earth observatio...

16 Claudio Persello, et al. ∙

research

∙ 11/15/2021

Large-Scale Hyperspectral Image Clustering Using Contrastive Learning

Clustering of hyperspectral images is a fundamental but challenging task...

0 Yaoming Cai, et al. ∙

research

∙ 11/15/2021

Fully Linear Graph Convolutional Networks for Semi-Supervised Learning and Clustering

This paper presents FLGC, a simple yet effective fully linear graph conv...

0 Yaoming Cai, et al. ∙

research

∙ 10/23/2020

Fusion of Dual Spatial Information for Hyperspectral Image Classification

The inclusion of spatial information into spectral classifiers for fine-...

20 Puhong Duan, et al. ∙

research

∙ 05/25/2020

Hyperspectral Image Classification with Attention Aided CNNs

Convolutional neural networks (CNNs) have been widely used for hyperspec...

14 Renlong Hang, et al. ∙

research

∙ 03/05/2020

Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep

Hyperspectral images provide detailed spectral information through hundr...

7 Behnood Rasti, et al. ∙

research

∙ 02/04/2020

Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

In this paper, we propose an efficient and effective framework to fuse h...

15 Renlong Hang, et al. ∙

research

∙ 12/18/2019

Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification

Up to the present, an enormous number of advanced techniques have been d...

22 Danfeng Hong, et al. ∙

research

∙ 10/26/2019

Deep Learning for Hyperspectral Image Classification: An Overview

Hyperspectral image (HSI) classification has become a hot topic in the f...

13 Shutao Li, et al. ∙

research

∙ 05/29/2019

Fusion of Heterogeneous Earth Observation Data for the Classification of Local Climate Zones

This paper proposes a novel framework for fusing multi-temporal, multisp...

0 Guichen Zhang, et al. ∙

research

∙ 02/28/2019

Cascaded Recurrent Neural Networks for Hyperspectral Image Classification

By considering the spectral signature as a sequence, recurrent neural ne...

10 Renlong Hang, et al. ∙

research

∙ 12/19/2018

Multisource and Multitemporal Data Fusion in Remote Sensing

The sharp and recent increase in the availability of data captured by di...

14 Pedram Ghamisi, et al. ∙

research

∙ 08/03/2017

Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Tehran metropolitan area in Iran

The SLEUTH model, based on the Cellular Automata (CA), can be applied to...

0 Shaghayegh Kargozar Nahavandya, et al. ∙

research

∙ 07/09/2017

Integration of LiDAR and Hyperspectral Data for Land-cover Classification: A Case Study

In this paper, an approach is proposed to fuse LiDAR and hyperspectral d...

0 Pedram Ghamisi, et al. ∙

Pedram Ghamisi

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