Dr. Rocco Sedona

I come from Venice, Italy and received my Master's Degree in Information Enginering at the University of Trento in 2019. My interests lie mainly in Deep Learning applied to Remote Sensing data and Distributed Deep Learning

Barakat, C., Riedel, M., Brynjólfsson, S., Cavallaro, G., Busch, J., & Sedona, R. (2021). Design and Evaluation of an HPC-based Expert System to speed-up Retail Data Analysis using Residual Networks Combined with Parallel Association Rule Mining and Scalable Recommenders. 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO), 248–253.

CAVALLARO, D.-I. G., Memon, M. S., & Sedona, R. (2020). Scalable Machine Learning with High Performance and Cloud Computing. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), FZJ-2020-04999.

Coquelin, D., Sedona, R., Riedel, M., & Götz, M. (2021). Evolutionary Optimization of Neural Architectures in Remote Sensing Classification Problems. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1587–1590.

Jitsev, J., Cherti, M., Langguth, M., Gong, B., Stadtler, S., Mozaffari, A., Cavallaro, G., Sedona, R., Schug, A., Strube, A., & others. (2021). JUWELS Booster–A Supercomputer for Large-Scale AI Research. High Performance Computing: ISC High Performance Digital 2021 International Workshops, Frankfurt Am Main, Germany, June 24-July 2, 2021, Revised Selected Papers, 12761, 453.

Kesselheim, S., Herten, A., Krajsek, K., Ebert, J., Jitsev, J., Cherti, M., Langguth, M., Gong, B., Stadtler, S., Mozaffari, A., & others. (2021). JUWELS Booster–A Supercomputer for Large-Scale AI Research. International Conference on High Performance Computing, 453–468.

Riedel, M, Einarsson, P., Hassanian, R., Book, M., Neukirchen, H., Sedona, R., Barakat, C., Cavallaro, G., Lintermann, A., Charaf, N., & others. (2021). 2021 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS, IPDPSW 2021-IN CONJUNCTION WITH IEEE IPDPS 2021.

Riedel, Morris, Sedona, R., Barakat, C., Einarsson, P., Hassanian, R., Cavallaro, G., Book, M., Neukirchen, H., & Lintermann, A. (2021). Practice and Experience in using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures. 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 76–85.

Sedona, R., Cavallaro, G., Jitsev, J., Strube, A., Riedel, M., & Benediktsson, J. A. (2019). Remote sensing big data classification with high performance distributed deep learning. Remote Sensing, 11(24), 3056.

Sedona, R., Cavallaro, G., Jitsev, J., Strube, A., Riedel, M., & Book, M. (2020). Scaling up a Multispectral RESNET-50 to 128 GPUs. IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium, 1058–1061.

Sedona, R., Cavallaro, G., Riedel, M., & Book, M. (2021). Enhancing Large Batch Size Training of Deep Models for Remote Sensing Applications. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1583–1586.

Sedona, R., Hoffmann, L., Spang, R., Cavallaro, G., Griessbach, S., Höpfner, M., Book, M., & Riedel, M. (2020a). Exploration of machine learning methods for the classification of infrared limb spectra of polar stratospheric clouds. Atmospheric Measurement Techniques, 13(7), 3661–3682.

Sedona, R., Hoffmann, L., Spang, R., Cavallaro, G., Griessbach, S., Höpfner, M., Book, M., & Riedel, M. (2020b). Using machine learning method to classify polar stratospheric cloud types from Envisat MIPAS observations. EGU General Assembly Conference Abstracts, 8103.

Sedona, R., & Jitsev, J. (n.d.). Remote Sensing Big Data Classification with High Performance Distributed Deep Learning.

Sedona, R., Paris, C., Cavallaro, G., Bruzzone, L., & Riedel, M. (2021). A High-Performance Multispectral Adaptation GAN for Harmonizing Dense Time Series of Landsat-8 and Sentinel-2 Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 10134–10146.