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Bidirectional Tree Decoder for HMER by ASIF RAZA is a document available to read on EtoBox.

This document presents a novel approach to Handwritten Mathematical Expression Recognition (HMER) by introducing the Mirror-Flipped Symbol Layout Tree (MF-SLT) and Bidirectional Asynchronous Training (BAT) techniques to enhance bidirectional context utilization in tree decoders. The proposed method improves the robustness and generalization of HMER models by analyzing the contributions of visual and linguistic perceptions separately and incorporating the Shared Language Modeling (SLM) mechanism. Experimenta

Author
ASIF RAZA
Language
EN