Evaluating classification and explainability in multimodal petrographic image analysis
arXiv:2611.10331v1 Announce Type: new Abstract: Automated thin-section classifiers increasingly combine plane-polarised and cross-polarised light (PPL and XPL), two complementary views central to petrographic identification. Classification accuracy alone does not reveal whether model errors reflect mineralogical…
Excerpt provided by arXiv cs.AI via its public feed. Full reporting belongs to the original publisher.
Read the full story on arXiv cs.AI
Related coverage
TechCrunch AI · 4m ago
PSI is trying to make a business out of AI-driven scientific discovery
The Decoder · 49m ago
Gemini 4 Carbon arrives just in time to feel like yesterdays news in the fastest model cycle yet
Ars Technica AI · 4h ago
DeepMind reveals Gemini Robotics 2.5 and open safety benchmark "ASIMOV-jailbreak"
Google DeepMind · 7h ago
Introducing AlphaProof Code: a breakthrough in verifying complex software at depth