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| author | jules@lens <julescarbon@gmail.com> | 2019-02-18 13:53:18 +0100 |
|---|---|---|
| committer | jules@lens <julescarbon@gmail.com> | 2019-02-18 13:53:18 +0100 |
| commit | 3fc5bb42b0dd94b56d0f11b1568d30a1ff835629 (patch) | |
| tree | 0a56e7f9cb84bda15a6e3074d1eba8312cc058f5 /site/datasets/citations/data_61.json | |
| parent | b28f65ad5016ba3c3c9f973bd2a64ea3c8a3f84c (diff) | |
rebuild everything
Diffstat (limited to 'site/datasets/citations/data_61.json')
| -rw-r--r-- | site/datasets/citations/data_61.json | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/site/datasets/citations/data_61.json b/site/datasets/citations/data_61.json index bfa12a44..f0fc38dc 100644 --- a/site/datasets/citations/data_61.json +++ b/site/datasets/citations/data_61.json @@ -1 +1 @@ -{"id": "563c940054e4b456661762c1ab858e6f730c3159", "paper": {"paperId": "563c940054e4b456661762c1ab858e6f730c3159", "key": "data_61", "title": "A Multi-modal Graphical Model for Scene Analysis", "journal": "2015 IEEE Winter Conference on Applications of Computer Vision", "address": "", "address_type": "", "lat": "", "lng": "", "pdf_link": "http://doi.ieeecomputersociety.org/10.1109/WACV.2015.139", "report_link": "papers/563c940054e4b456661762c1ab858e6f730c3159.html", "citation_count": 8, "citations_geocoded": 1, "citations_unknown": 7, "citations_empty": 0, "citations_pdf": 5, "citations_doi": 3, "name": "Data61 Pedestrian"}, "address": null, "citations": [["Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer", "", "University of Washington", "University of Washington", "University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA", "47.65432380", "-122.30800894", "edu", "", 2016]]}
\ No newline at end of file +{"id": "563c940054e4b456661762c1ab858e6f730c3159", "paper": {"paperId": "563c940054e4b456661762c1ab858e6f730c3159", "key": "data_61", "title": "A Multi-modal Graphical Model for Scene Analysis", "journal": "2015 IEEE Winter Conference on Applications of Computer Vision", "address": "", "address_type": "", "lat": "", "lng": "", "pdf_link": "http://www.nicta.com.au/wp-content/uploads/2015/02/TaghaviNaminetalWACV15.pdf", "report_link": "papers/563c940054e4b456661762c1ab858e6f730c3159.html", "citation_count": 8, "citations_geocoded": 2, "citations_unknown": 6, "citations_empty": 0, "citations_pdf": 5, "citations_doi": 3, "name": "Data61 Pedestrian"}, "address": null, "citations": [["MRF-Based Decision Fusion for Hyperspectral Image Classification", "Visionlab, University of Antwerp", "University of Gent", "Image Processing and Interpretation, University of Gent", "St. Pietersnieuwstraat 33, 9000 Gent, Belgium", "51.04656190", "3.72791810", "edu", "", "2018"], ["Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer", "", "University of Washington", "University of Washington", "University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA", "47.65432380", "-122.30800894", "edu", "", "2016"]]}
\ No newline at end of file |