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Hiba Najjar

Opening the Black Box: A systematic review on explainable artificial intelligence in remote sensing
2024 · Adrian Höhl, Ivica Obadic, et al. · IEEE Geoscience and Remote Sensing Magazine · 120
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Adaptive fusion of multi-modal remote sensing data for optimal sub-field crop yield prediction
2024 · Francisco Mena, Deepak Pathak, et al. · Remote Sensing of Environment · 112
Explainability of Subfield Level Crop Yield Prediction Using Remote Sensing
2025 · Hiba Najjar, Miro Miranda, et al. · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 43
Predicting Crop Yield with Machine Learning: An Extensive Analysis of Input Modalities and Models on a Field and Sub-Field Level
2023 · Deepak Pathak, Miro Miranda, et al. · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · 31
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PPIDomainMiner: Inferring domain-domain interactions from multiple sources of protein-protein interactions
2021 · Seyed Ziaeddine Alborzi, Amina Ahmed Nacer, et al. · PLoS Computational Biology · 29
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Unifying VXAI: A Systematic Review and Framework for the Evaluation of Explainable AI
2025 · Dembinsky, David, Lucieri, Adriano, et al. · arXiv (Cornell University) · 18
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Crop Yield Prediction: An Operational Approach to Crop Yield Modeling on Field and Subfield Level with Machine Learning Models
2023 · Patrick Helber, Benjamin Bischke, et al. · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · 16
Intrinsic explainability of multimodal learning for crop yield simulation
2025 · Hiba Najjar, Deepak Pathak, et al. · Computers and Electronics in Agriculture · 15
Explainable Multimodal Learning in Remote Sensing: Challenges and Future Directions
2024 · Alexander Günther, Hiba Najjar, et al. · IEEE Geoscience and Remote Sensing Letters · 14
Influence of Data Cleaning Techniques on Sub-Field Yield Predictions
2023 · Cristhian Sanchez, Deepak Pathak, et al. · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · 12
Feature Attribution Methods for Multivariate Time-Series Explainability in Remote Sensing
2023 · Hiba Najjar, Patrick Helber, et al. · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · 8
Web-based and machine learning approaches for identification of patient-reported outcomes in inflammatory bowel disease
2021 · Laetitia Ricci, Yannick Toussaint, et al. · Digestive and Liver Disease · 7
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Data-Centric Machine Learning for Earth Observation: Necessary and Sufficient Features
2026 · Hiba Najjar, Marlon Nuske, et al. · Communications in computer and information science · 5
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Xai-Guided Enhancement of Vegetation Indices for Crop Mapping
2024 · Hiba Najjar, Francisco Mena, et al. · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · 4
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YieldSAT: A Multimodal Benchmark Dataset for High-Resolution Crop Yield Prediction
2026 · Miranda, Miro, Pathak, Deepak, et al. · arXiv (Cornell University) · 2
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Can Multitask Learning Enhance Model Explainability?
2026 · Hiba Najjar, Bushra Alshbib, et al. · Lecture notes in computer science
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Real-Life Agricultural Data Retrieval for Large-Scale Annotation Flow Optimization
2022 · Hiba Najjar, Priyamvada Shankar, et al. · Algorithms for intelligent systems
PPIDomainMiner (PPIDM)
2021 · Alborzi Seyed Ziaeddine, Amina, Ahmed Nacer, et al. · Zenodo (CERN European Organization for Nuclear Research)
Works count: 20
Citation count: 430
H-index: 10
I10-index: 10
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