tiny-dnn documentations¶
tiny-dnn is a header only, dependency free deep learning library written in C++. It is designed to be used in the real applications, including IoT devices and embedded systems.
Table of Contents¶
Getting Started:
How-Tos:
Layers:
Examples(Link to github):
- MNIST image classification
- Cifar-10 image classification
- Deconvolutional Auto-encoder
- Importing Caffe’s model into tiny-dnn
Update Logs:
Developer Guides:
External Links¶
Here is the list of apps/papers using tiny-dnn. I’m willing to update this list if your software use tiny-dnn. Please contact me at nyanpn (at) gmail (dot) com.
Applications¶
- zhangqianhui/CnnForAndroid - A Vehicle Recognition Project using Convolutional Neural Network(CNN) in Android platform
- edgarriba/opencv_contrib (in progress) - A new opencv’s dnn module which use tiny-dnn as its backend
Papers¶
- S.S.Sarwar, S.Venkataramani, A.Raghunathan, and K.Roy, Multiplier-less Artificial Neurons Exploiting Error Resiliency for Energy-Efficient Neural Computing
- A.Viebke, Accelerated Deep Learning using Intel Xeon Phi
- Y.Xu, M.Berger, Q.Qian and E.O.Tuguldur, DAInamite - Team Description 2016
- K.Kim, H.Woo, Y.Han, K.Cho, H.Moon, D.Han, Diagnosis-Prescription System for Plant Disease using Mobile Device (Written in Korean)