Recent Publications

Adoni, W. Y. H., Lorenz, S., Fareedh, J. S., Gloaguen, R., & Bussmann, M. (2023). Investigation of Autonomous Multi-UAV Systems for Target Detection in Distributed Environment: Current Developments and Open Challenges. Drones, 7(4), 263.

Shahi, K. R., Ghamisi, P., Rasti, B., Gloaguen, R., & Scheunders, P. (2022). MS $^{2} $ A-Net: Multiscale Spectral–Spatial Association Network for Hyperspectral Image Clustering. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 6518-6530.

Lorenz, S., Thiele, S. T., Kirsch, M., Unger, G., Zimmermann, R., Guarnieri, P., ... & Gloaguen, R. (2022). Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland. Data, 7(8), 104.

De La Rosa, R., Tolosana-Delgado, R., Kirsch, M., & Gloaguen, R. (2022). Automated Multi-Scale and Multivariate Geological Logging from Drill-Core Hyperspectral Data. Remote Sensing, 14(11), 2676.

Xie, J., He, N., Fang, L. and Ghamisi, P., 2020. Multiscale Densely-Connected Fusion Networks for Hyperspectral Images Classification.

He, X., Wang, A., Ghamisi, P., Li, G. and Chen, Y., 2018. LiDAR Data Classification Using Spatial Transformation and CNN.

Othman, A., Al-Saady, Y., Al-Khafaji, A. and Gloaguen, R., 2013. Environmental change detection in the central part of Iraq using remote sensing data and GIS.

Booysen, R., Lorenz, S., Thiele, S., Fuchsloch, W., Marais, T., Nex, P. and Gloaguen, R., 2021. Accurate hyperspectral imaging of mineralised outcrops: An example from lithium-bearing pegmatites at Uis, Namibia.

Qiu, C., Schmitt, M., Mou, L., Ghamisi, P. and Zhu, X., 2018. Feature Importance Analysis for Local Climate Zone Classification Using a Residual Convolutional Neural Network with Multi-Source Datasets.

Sheikholeslami, M., Nadi, S., Naeini, A. and Ghamisi, P., 2020. An Efficient Deep Unsupervised Superresolution Model for Remote Sensing Images.

Pinter, G., Felde, I., Mosavi, A., Ghamisi, P. and Gloaguen, R., 2020. COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach.

Fuchs, M., Gloaguen, R., Merchel, S., Pohl, S., Sulaymonova, V., Andermann, C. and Rugel G., 2015. Millennial erosion rates across the Pamir based on 10Be concentrations in fluvial sediments: dominance of topographic over climatic factors.