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From the 1 of 10 linked papers with an AI index.

collaborators

10 papers

cs.CV2026

ST-LoRA: Single Trajectory LoRA Ensemble for Uncertainty Aware Agricultural Segmentation

Mohamed Farag, Genc Hoxha, Yahia Maleki +2

Reliable decision-support in digital agriculture requires accurate predictions and well-calibrated uncertainty estimates, particularly for dense prediction tasks such as semantic s…

cs.CV2026

Forecasting the Number of Harvest-ready Fruits of Sweet Peppers Using Multimodal Time-Series Data

Enrico Pallotta, Mohamed Farag, Esra Guclu +3

Accurate yield forecasting at the individual-plant level is critical for precision agriculture and supply-chain planning, yet public datasets capturing both visual growth dynamics…

cs.CV2026

Still image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels

Michael Halstead, Esra Guclu, Mohamed Farag +7

The paper introduces two new datasets of tomato plants captured by a robot—still images (BUTom21) and video sequences (BUTom-ST21)—with pixel‑level annotations for fruit detection,…

cs.CV2026

An assessment of data-centric methods for label noise identification in remote sensing data sets

Felix Kröber, Genc Hoxha, Ribana Roscher

Label noise in the sense of incorrect labels is present in many real-world data sets and is known to severely limit the generalizability of deep learning models. In the field of re…

cs.CV2025

Core-Set Selection for Data-efficient Land Cover Segmentation

Keiller Nogueira, Akram Zaytar, Wanli Ma +9

The increasing accessibility of remotely sensed data and their potential to support large-scale decision-making have driven the development of deep learning models for many Earth O…

cs.CV2025

LC-SLab -- An object-based deep learning framework for large-scale land cover classification from satellite imagery and sparse in-situ labels

Johannes Leonhardt, Juergen Gall, Ribana Roscher

Large-scale land cover maps generated using deep learning play a critical role across a wide range of Earth science applications. Open in-situ datasets from principled land cover s…