Domain Adaptation for Semantic Segmentation Using Convolutional Neural Networks. - Fabian Schenkel; Wolfgang Middelmann (IGARSS, 2019)

Hyperspectral Band Selection within a Deep Reinforcement Learning Framework. - Andreas Michel; Wolfgang Groß; Fabian Schenkel; Wolfgang Middelmann (IGARSS, 2020)

Domain Adaptation for Semantic Segmentation of Aerial Imagery Using Cycle-Consistent Adversarial Networks. - Fabian Schenkel; Wolfgang Middelmann (IGARSS, 2020)

Self-Supervised Image Colorization for Semantic Segmentation of Urban Land Cover. - Jonathan González-Santiago; Fabian Schenkel; Wolfgang Middelmann (IGARSS, 2021)

Class-aware Object Counting. - Andreas Michel; Wolfgang Gross; Fabian Schenkel; Wolfgang Middelmann (WACV (Workshops), 2022)

Deep Self-Supervised Pixel-Level Learning For Hyperspectral Classification. - Jonathan González-Santiago; Fabian Schenkel; Wolfgang Gross; Wolfgang Middelmann (WHISPERS, 2022)

DustNet: Attention to Dust. - Andreas Michel; Martin Weinmann; Fabian Schenkel; Tomas Gomez; Mark Falvey; Rainer Schmitz; Wolfgang Middelmann; Stefan Hinz (DAGM, 2023)

Deep Self-Supervised Hyperspectral-Lidar Fusion for Land Cover Classification. - Jonathan González-Santiago; Fabian Schenkel; Wolfgang Gross; Wolfgang Middelmann (IGARSS, 2023)

Terrestrial Visual Dust Density Estimation Based On Deep Learning. - Andreas Michel; Martin Weinmann; Fabian Schenkel; Thomas Gomez; Mark Falvey; Rainer Schmitz; Wolfgang Middelmann; Stefan Hinz (IGARSS, 2023)

Deep Self-Supervised Image Denoising for Joint Hyperspectral-Lidar Classification. - Jonathan González-Santiago; Wolfgang Gross; Fabian Schenkel; Wolfgang Middelmann (WHISPERS, 2023)

Domain Adaptation für die semantische Segmentierung unter Einbezug von biophysikalisch-spektralen Eigenschaften. - Fabian Schenkel (2024)