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Publications by - Ritu

Peer reviewed

Articles

[1]
R. Yadav et al., "Unsupervised flood detection on SAR time series using variational autoencoder," International Journal of Applied Earth Observation and Geoinformation, vol. 126, 2024.
[2]
R. Yadav, A. Nascetti and Y. Ban, "Deep attentive fusion network for flood detection on uni-temporal Sentinel-1 data," Frontiers in Remote Sensing, vol. 3, 2022.

Conference papers

[3]
R. Yadav, A. Nascetti and Y. Ban, "A CNN regression model to estimate buildings height maps using Sentinel-1 SAR and Sentinel-2 MSI time series," in Proceedings IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023.
[4]
A. Nascetti et al., "BioMassters : A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series," in Neural Information Processing Systems (NeurIPS 2023), 10-16 December, 2023, New Orleans, LA, USA, 2023.
[5]
A. Nascetti et al., "BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time Series," in Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023, 2023.
[6]
R. Yadav, A. Nascetti and Y. Ban, "Context-Aware Change Detection With Semi-Supervised Learning," in Proceedings IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023.
[7]
R. Yadav et al., "Self-Supervised Contrastive Model for Flood Mapping and Monitoring on SAR Time-Series," in EGU23 General Assembly, Vienna, Austria & Online, 23–28 April 2023, 2023.
[8]
R. Yadav, A. Nascetti and Y. Ban, "Attentive Dual Stream Siamese U-net for Flood Detection on Multi-temporal Sentinel-1 Data," in Proceedings IEEE International Geoscience and Remote Sensing Symposium IGARSS 2022, 2022, pp. 5222-5225.
[9]
R. Yadav, Y. Ban and A. Nascetti, "Building Change Detection using Multi-Temporal Airborne LiDAR Data," in Proceedings XXIV ISPRS Congress (2022 edition), 6–11 June 2022, Nice, France, 2022.

Non-peer reviewed

Theses

[10]
R. Yadav, "Supervised and Unsupervised Deep Learning Models for Flood Detection," Licentiate thesis Stockholm : KTH Royal Institute of Technology, TRITA-ABE-DLT, 2344, 2023.
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2024-06-16 04:32:30