Artificial intelligence (AI) increasingly supports subsurface characterization by integrating heterogeneous geophysical, geochemical, and spatial data. However, existing studies remain fragmented across disciplines and often leave unresolved questions about cross-modal physical coupling, fusion design, uncertainty prop...
H. Namazi, M. F. Sulaima, Ondrej Krejcar et al.· Environmental Earth Sciences· 0 citations
A limited bibliometric analysis of publications on geneticization studies is conducted to examine the changes in research topics and the critical content of the geneticization framework and introduces three new horizons to reconstruct and revise geneticization studies: medical humanities, philosophy of technology, and...
N. Ravan, H. Namazi· History and Philosophy of th...· 0 citations
Deep neural networks often suffer significant accuracy degradation when exposed to real-world image corruptions and distribution shifts. To overcome the limitations of fixed, input-agnostic test-time augmentation (TTA), an adaptive framework is proposed that learns per-sample transformations via reinforcement learning....
T. Mittal, A. Dubey, Dharmender Saini et al.· Scientific Reports· 0 citations
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