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cs.CV2023
SafeSea: Synthetic Data Generation for Adverse & Low Probability Maritime Conditions
Martin Tran, Jordan Shipard, Hermawan Mulyono +2
High-quality training data is essential for enhancing the robustness of object detection models. Within the maritime domain, obtaining a diverse real image dataset is particularly…
cs.CV2023★ 2 cited
Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable Diffusion
Jordan Shipard, Arnold Wiliem, Kien Nguyen Thanh +2
In this work, we investigate the problem of Model-Agnostic Zero-Shot Classification (MA-ZSC), which refers to training non-specific classification architectures (downstream models)…