Bengali Document Layout Analysis -- A YOLOV8 Based Ensembling Approach

arXiv:2309.00848v3 Announce Type: replace-cross
Abstract: This paper focuses on enhancing Bengali Document Layout Analysis (DLA) using the YOLOv8 model and innovative post-processing techniques. We tackle challenges unique to the complex Bengali script by employing data augmentation for model robustness. After meticulous validation set evaluation, we fine-tune our approach on the complete dataset, leading to a two-stage prediction strategy for accurate element segmentation. Our ensemble model, combined with post-processing, outperforms individual base architectures, addressing issues identified in the BaDLAD dataset. By …

abstract analysis arxiv augmentation challenges cs.cv cs.lg data dla document evaluation model robustness paper post-processing processing robustness script set type unique validation yolov8