278 citations · 1.5k across the 31 of their papers we have counts for
7 papers · 1 filter
Domain Generalization for Crop Segmentation with Standardized Ensemble Knowledge Distillation
Simone Angarano, Mauro Martini, Alessandro Navone +1
In recent years, precision agriculture has gradually oriented farming closer to automation processes to support all the activities related to field management. Service robotics pla…
Back-to-Bones: Rediscovering the Role of Backbones in Domain Generalization
Simone Angarano, Mauro Martini, Francesco Salvetti +2
Domain Generalization (DG) studies the capability of a deep learning model to generalize to out-of-training distributions. In the last decade, literature has been massively filled…
Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition
Vittorio Mazzia, Simone Angarano, Francesco Salvetti +2
Deep neural networks based purely on attention have been successful across several domains, relying on minimal architectural priors from the designer. In Human Action Recognition (…
Domain-Adversarial Training of Self-Attention Based Networks for Land Cover Classification using Multi-temporal Sentinel-2 Satellite Imagery
Mauro Martini, Vittorio Mazzia, Aleem Khaliq +1
The increasing availability of large-scale remote sensing labeled data has prompted researchers to develop increasingly precise and accurate data-driven models for land cover and c…
Efficient-CapsNet: Capsule Network with Self-Attention Routing
Vittorio Mazzia, Francesco Salvetti, Marcello Chiaberge
Deep convolutional neural networks, assisted by architectural design strategies, make extensive use of data augmentation techniques and layers with a high number of feature maps to…
Improvement in Land Cover and Crop Classification based on Temporal Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural Network (R-CNN)
Vittorio Mazzia, Aleem Khaliq, Marcello Chiaberge
The increasing spatial and temporal resolution of globally available satellite images, such as provided by Sentinel-2, creates new possibilities for researchers to use freely avail…
Real-Time Apple Detection System Using Embedded Systems With Hardware Accelerators: An Edge AI Application
Vittorio Mazzia, Francesco Salvetti, Aleem Khaliq +1
Real-time apple detection in orchards is one of the most effective ways of estimating apple yields, which helps in managing apple supplies more effectively. Traditional detection m…