all AI news
Contrastive Pretraining for Visual Concept Explanations of Socioeconomic Outcomes
April 16, 2024, 4:48 a.m. | Ivica Obadic, Alex Levering, Lars Pennig, Dario Oliveira, Diego Marcos, Xiaoxiang Zhu
cs.CV updates on arXiv.org arxiv.org
Abstract: Predicting socioeconomic indicators from satellite imagery with deep learning has become an increasingly popular research direction. Post-hoc concept-based explanations can be an important step towards broader adoption of these models in policy-making as they enable the interpretation of socioeconomic outcomes based on visual concepts that are intuitive to humans. In this paper, we study the interplay between representation learning using an additional task-specific contrastive loss and post-hoc concept explainability for socioeconomic studies. Our results on …
abstract adoption arxiv become concept concepts cs.cv deep learning interpretation making policy popular pretraining research satellite type visual visual concepts
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Business Data Analyst
@ Alstom | Johannesburg, GT, ZA