Hiba Najjar

Orcid: 0000-0002-7498-794X

According to our database1, Hiba Najjar authored at least 15 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2025
Can Multitask Learning Enhance Model Explainability?
CoRR, August, 2025

Intrinsic Explainability of Multimodal Learning for Crop Yield Prediction.
CoRR, August, 2025

Unifying VXAI: A Systematic Review and Framework for the Evaluation of Explainable AI.
CoRR, June, 2025

Explainability of Subfield Level Crop Yield Prediction Using Remote Sensing.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025

2024
Explainable Multimodal Learning in Remote Sensing: Challenges and Future Directions.
IEEE Geosci. Remote. Sens. Lett., 2024

Data-Centric Machine Learning for Earth Observation: Necessary and Sufficient Features.
CoRR, 2024

Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing.
CoRR, 2024

Opening the Black-Box: A Systematic Review on Explainable AI in Remote Sensing.
CoRR, 2024

Adaptive Fusion of Multi-view Remote Sensing data for Optimal Sub-field Crop Yield Prediction.
CoRR, 2024

Xai-Guided Enhancement of Vegetation Indices for Crop Mapping.
Proceedings of the IGARSS 2024, 2024

2023
Influence of Data Cleaning Techniques on Sub-Field Yield Predictions.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Predicting Crop Yield with Machine Learning: An Extensive Analysis of Input Modalities and Models on a Field and Sub-Field Level.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Feature Attribution Methods for Multivariate Time-Series Explainability in Remote Sensing.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Crop Yield Prediction: An Operational Approach to Crop Yield Modeling on Field and Subfield Level with Machine Learning Models.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2021
PPIDomainMiner: Inferring domain-domain interactions from multiple sources of protein-protein interactions.
PLoS Comput. Biol., 2021


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