An Innovative Framework for Supporting Remote Sensing in Image Processing Systems via Deep Transfer Learning

Autor: Oxana Korzh, Edoardo Serra, Ashish Sharma, Alfredo Cuzzocrea, Mikel Joaristi

Publikováno v: 2020 IEEE International Conference on Big Data (Big Data)
2020 IEEE International Conference on Big Data (Big Data), Dec 2020, Atlanta, United States. ⟨10.1109/bigdata50022.2020.9378306⟩
IEEE BigData

International audience; In this work, we propose a method based on Deep-Learning and Convolutional Neural Network (CNN) ensemble fine-tuning for the task of remote sensing imagery registration and processing. Our method is based on the CNN transfer l

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e6bed1c31d7b7a50d221eb5e5899049
https://hal.univ-lorraine.fr/hal-03284181

Unknown Landscape Identification with CNN Transfer Learning

Autor: Oxana Korzh, Ashish Sharma, Mikel Joaristi, Edoardo Serra

Publikováno v: ASONAM

Unknown landscape identification is the problem of identifying an unknown landscape from a set of already provided landscape images that are considered to be known. The aim of this work is to extract the intrinsic semantic of landscape images in orde

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::038afe06cccf7e82afe9199cef7c1fca
https://doi.org/10.1109/asonam.2018.8508357

Stacking approach for CNN transfer learning ensemble for remote sensing imagery

Autor: Timothy L. Andersen, Edoardo Serra, Oxana Korzh, Gregory Cook

Publikováno v: 2017 Intelligent Systems Conference (IntelliSys).

In this paper we propose a stacking approach for Convolutional Neural Network (CNN) transfer learning ensemble for remote sensing imagery, in particular for the task of scene classification. We propose to use a combination of features produced by an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d45ee7d5fbd75fff5a972d8a7ee2c60c
https://doi.org/10.1109/intellisys.2017.8324356