3 papers
cs.CV2025
A class-driven hierarchical ResNet for classification of multispectral remote sensing images
Giulio Weikmann, Gianmarco Perantoni, Lorenzo Bruzzone
This work presents a multitemporal class-driven hierarchical Residual Neural Network (ResNet) designed for modelling the classification of Time Series (TS) of multispectral images…
cs.CV2025
A deep multiple instance learning approach based on coarse labels for high-resolution land-cover mapping
Gianmarco Perantoni, Lorenzo Bruzzone
The quantity and the quality of the training labels are central problems in high-resolution land-cover mapping with machine-learning-based solutions. In this context, weak labels c…
cs.CV2025
Adaptive Gradient Calibration for Single-Positive Multi-Label Learning in Remote Sensing Image Scene Classification
Chenying Liu, Gianmarco Perantoni, Lorenzo Bruzzone +1
Multi-label classification (MLC) offers a more comprehensive semantic understanding of Remote Sensing (RS) imagery compared to traditional single-label classification (SLC). Howeve…