14 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Fall Detection for Smart Living using YOLOv5
Gracile Astlin Pereira
This work introduces a fall detection system using the YOLOv5mu model, which achieved a mean average precision (mAP) of 0.995, demonstrating exceptional accuracy in identifying fal…
cs.CV2024★ 14 cited
A Review of Transformer-Based Models for Computer Vision Tasks: Capturing Global Context and Spatial Relationships
Gracile Astlin Pereira, Muhammad Hussain
Transformer-based models have transformed the landscape of natural language processing (NLP) and are increasingly applied to computer vision tasks with remarkable success. These mo…
cs.CV2024★ 4 cited
Fall Detection for Industrial Setups Using YOLOv8 Variants
Gracile Astlin Pereira
This paper presents the development of an industrial fall detection system utilizing YOLOv8 variants, enhanced by our proposed augmentation pipeline to increase dataset variance an…