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This dataset consists of images from 53 AMOS webcams (https://mvrl.github.io/AMOS). The image sequences were selected so that they were stable so that a single sky/ground mask could be used for all images in a given camera. Contents [integer camera ID].zip : contains images from each camera skyfinder_masks.zip : contains the sky/ground masks Additional Links Project Webpage: https://cs.valdosta.edu/~rpmihail/skyfinder/ Another Dataset Summary: https://mvrl.github.io/SkyFinder Citation If you use this dataset, please cite the following paper: Mihail RP, Workman S, Bessinger Z, Jacobs N. 2016. Sky Segmentation in the Wild: An Empirical Study. In: IEEE Winter Conference on Applications of Computer Vision (WACV). 1–6. DOI: 10.1109/WACV.2016.7477637. @inproceedings{mihail2016sky, author = {Mihail, Radu Paul and Workman, Scott and Bessinger, Zach and Jacobs, Nathan}, booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)}, pages = {1--6}, doi = {10.1109/WACV.2016.7477637}, title = {Sky Segmentation in the Wild: An Empirical Study}, year = {2016} }
| selected citations These citations are derived from selected sources. 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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