This model obtains a top-1 accuracy 57.1% and a top-5 accuracy 80.2% on the validation set, using just the center crop.
(Using the average of 10 crops, (4 + 1 center) * 2 mirror, should obtain a bit higher accuracy.)
+This model was trained by Evan Shelhamer @shelhamer
+
## License
The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:
license: non-commercial
sha1: 405fc5acd08a3bb12de8ee5e23a96bec22f08204
caffe_commit: bc614d1bd91896e3faceaf40b23b72dab47d44f5
+gist_id: 866e2aa1fd707b89b913
---
This model is a replication of the model described in the [GoogleNet](http://arxiv.org/abs/1409.4842) publication. We would like to thank Christian Szegedy for all his help in the replication of GoogleNet model.
- Average Backward pass: 1123.84 ms.
- Average Forward-Backward: 1688.8 ms.
+This model was trained by Sergio Guadarrama @sguada
## License
This model obtains a top-1 accuracy 57.4% and a top-5 accuracy 80.4% on the validation set, using just the center crop.
(Using the average of 10 crops, (4 + 1 center) * 2 mirror, should obtain a bit higher accuracy still.)
+This model was trained by Jeff Donahue @jeffdonahue
+
## License
The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:
*N.B. For research purposes, make use of the official R-CNN package and not this example.*
+This model was trained by Ross Girshick @rbgirshick
+
## License
The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:
I1017 07:36:17.370730 31333 solver.cpp:247] Iteration 100000, Testing net (#0)
I1017 07:36:34.248730 31333 solver.cpp:298] Test net output #0: accuracy = 0.3916
+This model was trained by Sergey Karayev @sergeyk
+
## License
The Flickr Style dataset contains only URLs to images.