Added credits for training bvlc models

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Sergio 2014-12-20 23:24:32 -08:00
Родитель 4ba6efc7ac
Коммит b99e6cdcaf
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@ -18,6 +18,8 @@ The best validation performance during training was iteration 358,000 with valid
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. 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.) (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 ## 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: 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:

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@ -5,6 +5,7 @@ caffemodel_url: http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel
license: non-commercial license: non-commercial
sha1: 405fc5acd08a3bb12de8ee5e23a96bec22f08204 sha1: 405fc5acd08a3bb12de8ee5e23a96bec22f08204
caffe_commit: bc614d1bd91896e3faceaf40b23b72dab47d44f5 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. 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.
@ -25,6 +26,7 @@ Timings for bvlc_googlenet with cuDNN using batch_size:128 on a K40c:
- Average Backward pass: 1123.84 ms. - Average Backward pass: 1123.84 ms.
- Average Forward-Backward: 1688.8 ms. - Average Forward-Backward: 1688.8 ms.
This model was trained by Sergio Guadarrama @sguada
## License ## License

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@ -18,6 +18,8 @@ The best validation performance during training was iteration 313,000 with valid
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. 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.) (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 ## 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: 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:

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@ -13,6 +13,8 @@ Try the [detection example](http://nbviewer.ipython.org/github/BVLC/caffe/blob/m
*N.B. For research purposes, make use of the official R-CNN package and not this example.* *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 ## 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: 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:

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@ -15,6 +15,8 @@ The final performance:
I1017 07:36:17.370730 31333 solver.cpp:247] Iteration 100000, Testing net (#0) 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 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 ## License
The Flickr Style dataset contains only URLs to images. The Flickr Style dataset contains only URLs to images.