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MULTIMAE MEETS EARTH OBSERVATION: PRE-TRAINING MULTI-MODAL MULTI-TASK MASKED AUTOENCODERS FOR EARTH OBSERVATION TASKS (APPENDIX)

O1-mini prompt to expose the seven components of agricultural disease management evaluation framework

This work investigates Source-Free Domain Adaptation (SFDA), where a model adapts to a target domain without access to source data. A new augmentation technique, Shuffle PatchMix (SPM), and a novel reweighting strategy are introduced to enhance performance. SPM shuffles and blends image patches to generate diverse and challenging augmentations, while the reweighting strategy prioritizes reliable pseudo-labels to mitigate label noise. These techniques are particularly effective on smaller datasets like PACS, where overfitting and pseudo-label noise pose greater risks.

This supplementary material presents detailed transformer model architectures, training parameters, and comprehensive evaluation metrics to complement our comparison of RNN and transformer models for Indonesian news classification. Our analysis provides deeper insights into why transformer models outperform RNN approaches despite their larger parameter counts.

Supp ro TASE 2025 submission

Supplemental Material

Supplement for the research paper: A PHYSICS-GUIDED SMOOTHING METHOD FOR MATERIAL MODELING WITH DIGITAL IMAGE CORRELATION (DIC) MEASUREMENTS

This document contains the supplementary material for the ICIP_2050 paper with ID #2494 and title "An End-to-End Class-Aware and Attention-Guided Model for Object State Classification".

Supplementary materials for paper Pose-free 3D Gaussian Splatting via Shape-Ray Estimation

Abstract