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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Image Processing Techniques and Applications
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
fundfunder
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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

350 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
350 works in the cohort · of 4,299,418page 1 of 7

Labels cover 0 of 350 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 350 of 350 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affunlabeled
High-quality computational imaging through simple lenses
Felix Heide, Mushfiqur Rouf, Matthias B. Hullin, Björn Labitzke, Wolfgang Heidrich, Andreas Kolb
2013· article· en· ACM Transactions on Graphics· Engineering
machine prediction:candidate · noneconsensus · none
210
citations
affunlabeled
LBP-Based Segmentation of Defocus Blur
Yi Xin, Mark Eramian
2016· article· en· IEEE Transactions on Image Processing· Engineering
machine prediction:candidate · noneconsensus · none
148
citations
affno abstractunlabeled
Depth from Defocus Estimation in Spatial Domain
Djemel Ziou, F. Deschênes
2001· article· en· Computer Vision and Image Understanding· Engineering
machine prediction:candidate · noneconsensus · none
60
citations
affno abstractunlabeled
Confocal Stereo
Samuel W. Hasinoff, Kiriakos N. Kutulakos
2008· article· en· International Journal of Computer Vision· Engineering
machine prediction:candidate · noneconsensus · none
55
citations
afffundunlabeled
Light-Efficient Photography
Samuel W. Hasinoff, Kiriakos N. Kutulakos
2011· article· en· IEEE Transactions on Pattern Analysis and Machine Intelligence· Engineering
machine prediction:candidate · noneconsensus · none
53
citations
afffundunlabeled
Depth from Defocus in the Wild
Huixuan Tang, Scott Cohen, Brian Price, Stephen Schiller, Kiriakos N. Kutulakos
2017· article· en· Engineering
machine prediction:candidate · noneconsensus · none
46
citations
affno abstractunlabeled
Confocal Stereo
Samuel W. Hasinoff, Kiriakos N. Kutulakos
2006· book-chapter· en· Lecture notes in computer science· Engineering
machine prediction:candidate · noneconsensus · none
44
citations
affno abstractunlabeled
Coded Two-Bucket Cameras for Computer Vision
Mian Wei, Navid Sarhangnejad, Zhengfan Xia, Nikita Gusev, Nikola Katic, Roman Genov +1 more
2018· book-chapter· en· Lecture notes in computer science· Engineering
machine prediction:candidate · noneconsensus · none
28
citations
affno abstractunlabeled
Light-Efficient Photography
Samuel W. Hasinoff, Kiriakos N. Kutulakos
2008· book-chapter· en· Lecture notes in computer science· Engineering
machine prediction:candidate · noneconsensus · none
26
citations
afffundno abstractunlabeled
Revisiting Autofocus for Smartphone Cameras
Abdullah Abuolaim, Abhijith Punnappurath, Michael S. Brown
2018· book-chapter· en· Lecture notes in computer science· Engineering
machine prediction:candidate · noneconsensus · none
24
citations
affno abstractunlabeled
Machine vision system for curved surface inspection
Min‐Fan Ricky Lee, Clarence W. de Silva, Elizabeth A. Croft, Q. M. Jonathan Wu
2000· article· en· Machine Vision and Applications· Engineering
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
Blur‐Aware Image Downsampling
Matthew Trentacoste, Rafał Mantiuk, Wolfgang Heidrich
2011· article· en· Computer Graphics Forum· Engineering
machine prediction:candidate · noneconsensus · none
22
citations

How this was built: Screen · Findings · About