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20192024
most citedThe Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery

17 citations · 36 across the 18 of their papers we have counts for

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Showing 2024Show all

2 papers · 1 filter

cs.CV2024

Towards Open-World Object-based Anomaly Detection via Self-Supervised Outlier Synthesis

Brian K. S. Isaac-Medina, Yona Falinie A. Gaus, Neelanjan Bhowmik +1

Object detection is a pivotal task in computer vision that has received significant attention in previous years. Nonetheless, the capability of a detector to localise objects out o…

cs.CV2024

Performance Evaluation of Segment Anything Model with Variational Prompting for Application to Non-Visible Spectrum Imagery

Yona Falinie A. Gaus, Neelanjan Bhowmik, Brian K. S. Isaac-Medina +1

The Segment Anything Model (SAM) is a deep neural network foundational model designed to perform instance segmentation which has gained significant popularity given its zero-shot s…