20 citations · 35 across the 3 of their papers we have counts for
5 papers
Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI
Vladimir Zaigrajew, Hubert Baniecki, Lukasz Tulczyjew +4
Remote sensing (RS) applications in the space domain demand machine learning (ML) models that are reliable, robust, and quality-assured, making red teaming a vital approach for ide…
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing
Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé +2
Hyperspectral unmixing remains one of the most challenging tasks in the analysis of such data. Deep learning has been blooming in the field and proved to outperform other classic u…
Graph Neural Networks Extract High-Resolution Cultivated Land Maps from Sentinel-2 Image Series
Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé +2
Maintaining farm sustainability through optimizing the agricultural management practices helps build more planet-friendly environment. The emerging satellite missions can acquire m…
Segmenting Hyperspectral Images Using Spectral-Spatial Convolutional Neural Networks With Training-Time Data Augmentation
Jakub Nalepa, Lukasz Tulczyjew, Michal Myller +1
Hyperspectral imaging provides detailed information about the scanned objects, as it captures their spectral characteristics within a large number of wavelength bands. Classificati…
Band Selection from Hyperspectral Images Using Attention-based Convolutional Neural Networks
Pablo Ribalta Lorenzo, Lukasz Tulczyjew, Michal Marcinkiewicz +1
This paper introduces new attention-based convolutional neural networks for selecting bands from hyperspectral images. The proposed approach re-uses convolutional activations at di…