2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Performance of computer vision algorithms for fine-grained classification using crowdsourced insect images
Rita Pucci, Vincent J. Kalkman, Dan Stowell
With fine-grained classification, we identify unique characteristics to distinguish among classes of the same super-class. We are focusing on species recognition in Insecta, as the…
cs.CV2024★ 2 cited
COOD: Combined out-of-distribution detection using multiple measures for anomaly & novel class detection in large-scale hierarchical classification
L. E. Hogeweg, R. Gangireddy, D. Brunink +3
High-performing out-of-distribution (OOD) detection, both anomaly and novel class, is an important prerequisite for the practical use of classification models. In this paper, we fo…
cs.CV2023★ 1 cited
Comparison between transformers and convolutional models for fine-grained classification of insects
Rita Pucci, Vincent J. Kalkman, Dan Stowell
Fine-grained classification is challenging due to the difficulty of finding discriminatory features. This problem is exacerbated when applied to identifying species within the same…