https://hackerpaper.kaipfister.de/p/1310.1531/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=16169058urn:hackerpapers:mention:1310.1531:16169058Wed, 17 Jan 2018 16:14:57 GMT<p>Figure 4 of the The Decaf paper shows meaningful learning w/ only 10 examples! https://arxiv.org/abs/1310.1531</p><p><a href="https://hackerpaper.kaipfister.de/p/1310.1531/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CVhttps://news.ycombinator.com/item?id=6856414urn:hackerpapers:mention:1310.1531:6856414Thu, 05 Dec 2013 19:07:32 GMT<p>There is also DeCAF, which actually includes a way to load a pretrained ImageNet network based on cuda-convnet. I have had pretty recent success using this blob as preprocessing for image classification, ala http://arxiv.org/abs/1310.1531. Github is here: https://github.com/UCB-ICSI-Vision-Group/decaf-release/ My current code as an example of combining sklearn/pylearn2 with DeCAF preprocessing (under the decaf folder, sklearn usage is under previous commits): https://github.com/kastnerkyle/kaggle-dogs-vs-cats</p><p><a href="https://hackerpaper.kaipfister.de/p/1310.1531/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CV