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S. Lahrichi

4 papers hereh-index 4128 citations12 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

cs.CV2026

Global Building Area Estimation Products: How Accurate Are They?

Saad Lahrichi, Doa'a Allabadi, Kyle Bradbury +1

Geo-spatial rasters of building footprint area are useful for a variety of tasks, such as monitoring urbanization, improving energy efficiency, and tracking greenhouse gas emission…

cs.CV2025

Improved Wildfire Spread Prediction with Time-Series Data and the WSTS+ Benchmark

Saad Lahrichi, Jake Bova, Jesse Johnson +1

Recent research has demonstrated the potential of deep neural networks (DNNs) to accurately predict wildfire spread on a given day based upon high-dimensional explanatory data from…

cs.CV2025

Is Self-Supervised Pre-training on Satellite Imagery Better than ImageNet? A Systematic Study with Sentinel-2

Saad Lahrichi, Zion Sheng, Shufan Xia +2

Self-supervised learning (SSL) has demonstrated significant potential in pre-training robust models with limited labeled data, making it particularly valuable for remote sensing (R…

cs.LG2024

Does Deep Active Learning Work in the Wild?

Simiao Ren, Saad Lahrichi, Yang Deng +3

Deep active learning (DAL) methods have shown significant improvements in sample efficiency compared to simple random sampling. While these studies are valuable, they nearly always…

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