5 citations · 8 across the 4 of their papers we have counts for
5 papers
Attentive Weakly Supervised land cover mapping for object-based satellite image time series data with spatial interpretation
Dino Ienco, Yawogan Jean Eudes Gbodjo, Roberto Interdonato +1
Nowadays, modern Earth Observation systems continuously collect massive amounts of satellite information. The unprecedented possibility to acquire high resolution Satellite Image T…
Fine grained classification for multi-source land cover mapping
Yawogan Jean Eudes Gbodjo, Dino Ienco, Louise Leroux +2
Nowadays, there is a general agreement on the need to better characterize agricultural monitoring systems in response to the global changes. Timely and accurate land use/land cover…
Object-based multi-temporal and multi-source land cover mapping leveraging hierarchical class relationships
Yawogan Jean Eudes Gbodjo, Dino Ienco, Louise Leroux +4
European satellite missions Sentinel-1 (S1) and Sentinel-2 (S2) provide at highspatial resolution and high revisit time, respectively, radar and optical imagesthat support a wide r…
Supervised level-wise pretraining for recurrent neural network initialization in multi-class classification
Dino Ienco, Roberto Interdonato, Raffaele Gaetano
Recurrent Neural Networks (RNNs) can be seriously impacted by the initial parameters assignment, which may result in poor generalization performances on new unseen data. With the o…
Combining Sentinel-1 and Sentinel-2 Time Series via RNN for object-based land cover classification
Dino Ienco, Raffaele Gaetano, Roberto Interdonato +2
Radar and Optical Satellite Image Time Series (SITS) are sources of information that are commonly employed to monitor earth surfaces for tasks related to ecology, agriculture, mobi…