caffe-cvprw15-master
所属分类：人工智能/神经网络/深度学习
开发工具：Visual C++
文件大小：7232KB
下载次数：7
上传日期：2018-01-01 12:07:02
上 传 者：
cumtstrive
说明： 基于深度学习框架构建用于快速图像检索的二值哈希编码
(Construction of binary hash codes for fast image retrieval based on depth learning framework)
文件列表:
.Doxyfile (101863, 2016-01-13)
.travis.yml (1325, 2016-01-13)
CMakeLists.txt (2659, 2016-01-13)
CMakeScripts (0, 2016-01-13)
CMakeScripts\FindAtlas.cmake (1567, 2016-01-13)
CMakeScripts\FindGFlags.cmake (1315, 2016-01-13)
CMakeScripts\FindGlog.cmake (1255, 2016-01-13)
CMakeScripts\FindLAPACK.cmake (6723, 2016-01-13)
CMakeScripts\FindLMDB.cmake (1015, 2016-01-13)
CMakeScripts\FindLevelDB.cmake (1398, 2016-01-13)
CMakeScripts\FindMKL.cmake (3553, 2016-01-13)
CMakeScripts\FindOpenBLAS.cmake (1539, 2016-01-13)
CMakeScripts\FindSnappy.cmake (700, 2016-01-13)
CMakeScripts\lint.cmake (1450, 2016-01-13)
CONTRIBUTORS.md (620, 2016-01-13)
INSTALL.md (197, 2016-01-13)
LICENSE (2083, 2016-01-13)
Makefile (20360, 2016-01-13)
Makefile.config (2613, 2016-01-13)
Makefile.config.example (2602, 2016-01-13)
analysis (0, 2016-01-13)
analysis\BRE-p-at-k.txt (58, 2016-01-13)
analysis\CNNH+-p-at-k.txt (60, 2016-01-13)
analysis\CNNH-p-at-k.txt (60, 2016-01-13)
analysis\ITQ-CCA-p-at-k.txt (59, 2016-01-13)
analysis\ITQ-p-at-k.txt (58, 2016-01-13)
analysis\KSH-p-at-k.txt (57, 2016-01-13)
analysis\LSH-p-at-k.txt (59, 2016-01-13)
analysis\MLH-p-at-k.txt (58, 2016-01-13)
analysis\SH-p-at-k.txt (55, 2016-01-13)
analysis\plot-p-at-k.gnuplot (1155, 2016-01-13)
analysis\precision.m (1404, 2016-01-13)
caffe.cloc (1180, 2016-01-13)
data (0, 2016-01-13)
data\cifar10 (0, 2016-01-13)
data\cifar10\get_cifar10.sh (504, 2016-01-13)
data\ilsvrc12 (0, 2016-01-13)
... ...
---
name: BVLC Reference RCNN ILSVRC13 Model
caffemodel: bvlc_reference_rcnn_ilsvrc13.caffemodel
caffemodel_url: http://dl.caffe.berkeleyvision.org/bvlc_reference_rcnn_ilsvrc13.caffemodel
license: non-commercial
sha1: bdd8abb885819cba5e2fe1eb36235f2319477e***
caffe_commit: a7e397abbda52c0b90323c23ab95bdeabee90a***
---
The pure Caffe instantiation of the [R-CNN](https://github.com/rbgirshick/rcnn) model for ILSVRC13 detection.
This model was made by transplanting the R-CNN SVM classifiers into a `fc-rcnn` classification layer, provided here as an off-the-shelf Caffe detector.
Try the [detection example](http://nbviewer.ipython.org/github/BVLC/caffe/blob/master/examples/detection.ipynb) to see it in action.
*N.B. For research purposes, make use of the official R-CNN package and not this example.*
## 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:
"Researcher shall use the Database only for non-commercial research and educational purposes."
Accordingly, this model is distributed under a non-commercial license.
近期下载者：
相关文件：
收藏者：