Search Results for author: Roberto Interdonato

Found 8 papers, 3 papers with code

Enriching Epidemiological Thematic Features For Disease Surveillance Corpora Classification

no code implementations LREC 2022 Edmond Menya, Mathieu Roche, Roberto Interdonato, Dickson Owuor

We find these thematic features rich enough to improve epidemiological document classification over a smaller data set than initially used in PADI-Web classifier.

Classification Document Classification +2

An evaluation framework for comparing epidemic intelligence systems

1 code implementation30 Mar 2023 Nejat Arinik, Roberto Interdonato, Mathieu Roche, Maguelonne Teisseire

In the context of Epidemic Intelligence, many Event-Based Surveillance (EBS) systems have been proposed in the literature to promote the early identification and characterization of potential health threats from online sources of any nature.

Descriptive

Fine grained classification for multi-source land cover mapping

1 code implementation4 Apr 2020 Yawogan Jean Eudes Gbodjo, Dino Ienco, Louise Leroux, Roberto Interdonato, Raffaelle Gaetano

Nowadays, there is a general agreement on the need to better characterize agricultural monitoring systems in response to the global changes.

Classification General Classification

Object-based multi-temporal and multi-source land cover mapping leveraging hierarchical class relationships

1 code implementation20 Nov 2019 Yawogan Jean Eudes Gbodjo, Dino Ienco, Louise Leroux, Roberto Interdonato, Raffaele Gaetano, Babacar Ndao, Stephane Dupuy

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 range of Earth surface monitoring tasks such as LandUse/Land Cover mapping.

Specificity Time Series +1

Supervised level-wise pretraining for recurrent neural network initialization in multi-class classification

no code implementations4 Nov 2019 Dino Ienco, Roberto Interdonato, Raffaele Gaetano

To the best of our knowledge, despite the great interest in RNN-based classification, this is the first data-aware strategy dealing with the initialization of such models.

Classification General Classification +3

DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn

no code implementations20 Sep 2018 Roberto Interdonato, Dino Ienco, Raffaele Gaetano, Kenji Ose

In this work, we propose the first deep learning architecture for the analysis of SITS data, namely \method{} (DUal view Point deep Learning architecture for time series classificatiOn), that combines Convolutional and Recurrent neural networks to exploit their complementarity.

Earth Observation General Classification +4

Topology-driven Diversity for Targeted Influence Maximization with Application to User Engagement in Social Networks

no code implementations20 Apr 2018 Antonio Caliò, Roberto Interdonato, Chiara Pulice, Andrea Tagarelli

However, little attention has been paid to the fact that the success of an information diffusion campaign might depend not only on the number of the initial influencers to be detected but also on their diversity w. r. t.

Social and Information Networks Physics and Society

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