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Publicações

Publicações por Rita Paula Ribeiro

2019

ECML PKDD 2018 Workshops

Autores
Monreale, A; Alzate, C; Kamp, M; Krishnamurthy, Y; Paurat, D; Sayed-Mouchaweh, M; Bifet, A; Gama, J; Ribeiro, RP;

Publicação
Communications in Computer and Information Science

Abstract

2021

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Autores
Kamp, M; Koprinska, I; Bibal, A; Bouadi, T; Frénay, B; Galárraga, L; Oramas, J; Adilova, L; Krishnamurthy, Y; Kang, B; Largeron, C; Lijffijt, J; Viard, T; Welke, P; Ruocco, M; Aune, E; Gallicchio, C; Schiele, G; Pernkopf, F; Blott, M; Fröning, H; Schindler, G; Guidotti, R; Monreale, A; Rinzivillo, S; Biecek, P; Ntoutsi, E; Pechenizkiy, M; Rosenhahn, B; Buckley, C; Cialfi, D; Lanillos, P; Ramstead, M; Verbelen, T; Ferreira, PM; Andresini, G; Malerba, D; Medeiros, I; Fournier-Viger, P; Nawaz, MS; Ventura, S; Sun, M; Zhou, M; Bitetta, V; Bordino, I; Ferretti, A; Gullo, F; Ponti, G; Severini, L; Ribeiro, R; Gama, J; Gavaldà, R; Cooper, L; Ghazaleh, N; Richiardi, J; Roqueiro, D; Saldana Miranda, D; Sechidis, K; Graça, G;

Publicação
Communications in Computer and Information Science

Abstract

2021

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Autores
Kamp, M; Koprinska, I; Bibal, A; Bouadi, T; Frénay, B; Galárraga, L; Oramas, J; Adilova, L; Krishnamurthy, Y; Kang, B; Largeron, C; Lijffijt, J; Viard, T; Welke, P; Ruocco, M; Aune, E; Gallicchio, C; Schiele, G; Pernkopf, F; Blott, M; Fröning, H; Schindler, G; Guidotti, R; Monreale, A; Rinzivillo, S; Biecek, P; Ntoutsi, E; Pechenizkiy, M; Rosenhahn, B; Buckley, C; Cialfi, D; Lanillos, P; Ramstead, M; Verbelen, T; Ferreira, PM; Andresini, G; Malerba, D; Medeiros, I; Fournier-Viger, P; Nawaz, MS; Ventura, S; Sun, M; Zhou, M; Bitetta, V; Bordino, I; Ferretti, A; Gullo, F; Ponti, G; Severini, L; Ribeiro, R; Gama, J; Gavaldà, R; Cooper, L; Ghazaleh, N; Richiardi, J; Roqueiro, D; Saldana Miranda, D; Sechidis, K; Graça, G;

Publicação
Communications in Computer and Information Science

Abstract

2023

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Autores
Koprinska, I; Mignone, P; Guidotti, R; Jaroszewicz, S; Fröning, H; Gullo, F; Ferreira, PM; Roqueiro, D; Ceddia, G; Nowaczyk, S; Gama, J; Ribeiro, R; Gavaldà, R; Masciari, E; Ras, Z; Ritacco, E; Naretto, F; Theissler, A; Biecek, P; Verbeke, W; Schiele, G; Pernkopf, F; Blott, M; Bordino, I; Danesi, IL; Ponti, G; Severini, L; Appice, A; Andresini, G; Medeiros, I; Graça, G; Cooper, L; Ghazaleh, N; Richiardi, J; Saldana, D; Sechidis, K; Canakoglu, A; Pido, S; Pinoli, P; Bifet, A; Pashami, S;

Publicação
Communications in Computer and Information Science

Abstract

2023

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Autores
Koprinska, I; Mignone, P; Guidotti, R; Jaroszewicz, S; Fröning, H; Gullo, F; Ferreira, PM; Roqueiro, D; Ceddia, G; Nowaczyk, S; Gama, J; Ribeiro, R; Gavaldà, R; Masciari, E; Ras, Z; Ritacco, E; Naretto, F; Theissler, A; Biecek, P; Verbeke, W; Schiele, G; Pernkopf, F; Blott, M; Bordino, I; Danesi, IL; Ponti, G; Severini, L; Appice, A; Andresini, G; Medeiros, I; Graça, G; Cooper, L; Ghazaleh, N; Richiardi, J; Saldana, D; Sechidis, K; Canakoglu, A; Pido, S; Pinoli, P; Bifet, A; Pashami, S;

Publicação
Communications in Computer and Information Science

Abstract

2024

More (Enough) Is Better: Towards Few-Shot Illegal Landfill Waste Segmentation

Autores
Molina, M; Veloso, B; Ferreira, CA; Ribeiro, RP; Gama, J;

Publicação
Frontiers in Artificial Intelligence and Applications - ECAI 2024

Abstract
Image segmentation for detecting illegal landfill waste in aerial images is essential for environmental crime monitoring. Despite advancements in segmentation models, the primary challenge in this domain is the lack of annotated data due to the unknown locations of illegal waste disposals. This work mainly focuses on evaluating segmentation models for identifying individual illegal landfill waste segments using limited annotations. This research seeks to lay the groundwork for a comprehensive model evaluation to contribute to environmental crime monitoring and sustainability efforts by proposing to harness the combination of agnostic segmentation and supervised classification approaches. We mainly explore different metrics and combinations to better understand how to measure the quality of this applied segmentation problem.

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