Author

S. Remya

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Open access Sep 2026

A unified multi-modal latent diffusion framework with modality-dropout training

A unified latent diffusion framework that addresses both limitations simultaneously, indicating that adaptive modality weighting outperforms fixed conditioning strategies and that modality-dropout training provides an effective partial-conditioning robustness mechanism.

S. Remya, Manu J. Pillai, Laveena Herman et al. · Frontiers in Artificial Inte... · 0 citations

Open access Jul 2026

A deep learning perception framework for farm digital twins: weed species classification, semantic segmentation, and gradient-based visual interpretability

This paper presents a tri-component deep learning framework designed explicitly as a perception and interpretability layer for Farm Digital Twin architectures, evaluated on a five-species balanced subset of the Moving Fields Weed Dataset (MFWD)—a publicly available benchmark of 94K high-resolution images of 28 weed spe...

Anusree Manoj, Aiswarya S. Kumar, S. Remya et al. · Frontiers in Sustainable Foo... · 0 citations