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{"references": ["Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2021). High-Resolution Image Synthesis with Latent Diffusion Models. arXiv. https://doi.org/10.48550/arXiv.2112.10752", "Ruiz, N., Li, Y., Jampani, V., Pritch, Y., Rubinstein, M., & Aberman, K. (2022). DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation. arXiv. https://doi.org/10.48550/arXiv.2208.12242"]}
Geo Fossils-I is a synthetic dataset of fossil images that can be a pioneer in solving the limited availability of Image Classification and Object Detection on 2D images from geological outcrops. The dataset consists of six different fossil types found in geological outcrops, with 200 images per class, for a total of 1200 fossil images.
Synthetic Data, Fossils, Computer Vision, Geology, FOS: Earth and related environmental sciences, Outcrops
Synthetic Data, Fossils, Computer Vision, Geology, FOS: Earth and related environmental sciences, Outcrops
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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