Caffe Tutorial – Caffe (Software)
Created by Yangqing Jia Lead Developer Evan Shelhamer travelhome.vntravelhome.vn is a deep learning framework made with expression, speed, and modularity in mind.It is developed by Berkeley AI Research (BAIR) and by community contributors.Yangqing Jia created the project during his PhD at UC Berkeley.travelhome.vn is released under the BSD 2-Clause license.
Đang xem: Caffe
Check out our web image classification demo!
Why travelhome.vn?
Expressive architecture encourages application and innovation.Models and optimization are defined by configuration without hard-coding.Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices.
Extensible code fosters active development.In travelhome.vn’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back.Thanks to these contributors the framework tracks the state-of-the-art in both code and models.
Speed makes travelhome.vn perfect for research experiments and industry deployment.travelhome.vn can process over 60M images per day with a single NVIDIA K40 GPU*.That’s 1 ms/image for inference and 4 ms/image for learning and more recent library versions and hardware are faster still.We believe that travelhome.vn is among the fastest convnet implementations available.
Community: travelhome.vn already powers academic research projects, startup prototypes, and even large-scale industrial applications in vision, speech, and multimedia.Join our community of brewers on the travelhome.vn-users group and Github.
* With the ILSVRC2012-winning SuperVision model and prefetching IO.
Documentation
Notebook Examples
Command Line Examples
Citing travelhome.vn
Please cite travelhome.vn in your publications if it helps your research:
article{jia2014travelhome.vn, Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor}, Journal = {arXiv preprint arXiv:1408.5093}, Title = {travelhome.vn: Convolutional Architecture for Fast Feature Embedding}, Year = {2014}}
If you do publish a paper where travelhome.vn helped your research, we encourage you to cite the framework for tracking by Google Scholar.
Xem thêm: “Sang Trọng Bậc Nhất” Với Top 5 Nhà Hàng Tiệc Cưới Sang Trọng
Contacting Us
Join the travelhome.vn-users group to ask questions and discuss methods and models. This is where we talk about usage, installation, and applications.
Framework development discussions and thorough bug reports are collected on Issues.
Acknowledgements
The BAIR travelhome.vn developers would like to thank NVIDIA for GPU donation, A9 and Amazon Web Services for a research grant in support of travelhome.vn development and reproducible research in deep learning, and BAIR PI Trevor Darrell for guidance.
The BAIR members who have contributed to travelhome.vn are (alphabetical by first name):Carl Doersch, Eric Tzeng, Evan Shelhamer, Jeff Donahue, Jon Long, Philipp Krähenbühl, Ronghang Hu, Ross Girshick, Sergey Karayev, Sergio Guadarrama, Takuya Narihira, and Yangqing Jia.
The open-source community plays an important and growing role in travelhome.vn’s development.Check out the Github project pulse for recent activity and the contributors for the full list.
We sincerely appreciate your interest and contributions!If you’d like to contribute, please read the developing & contributing guide.
Xem thêm: Trà Sữa Popping Tea – Thực Đơn Giao Hàng Tận Nơi Của Popping Tea
Yangqing would like to give a personal thanks to the NVIDIA Academic program for providing GPUs, Oriol Vinyals for discussions along the journey, and BAIR PI Trevor Darrell for advice.
Bình luận