资源分类
》 资源 》算法》Mixture DCNN

Mixture DCNN

2019-09-20 | |  37 |   0 |   0

Mixture DCNN is a novel multi-model architecture which achieves better performance than an ensemble of DCNNs as evaluated on three different fine-grained datasets. Please cite the following paper if you use these models in your research.

@inproceedings{GeWACV2016,
author = {ZongYuan Ge and Alex Bewley and Christopher McCool and Ben Upcroft and Peter Corke and Conrad Sanderson},
title = {Fine-Grained Classification via Mixture of Deep Convolutional Neural Networks},
booktitle = {Winter Conference on the Applications of Computer Vision (WACV)},
publisher = {IEEE},
year = {2016}
}

* Models
* Paper

无链接

上一篇：SqueezeNet

下一篇：Mulimodal Compact Bilinear Pooling for VQA

用户评价
全部评价

热门资源

  • seetafaceJNI

    项目介绍 基于中科院seetaface2进行封装的JAVA...

  • spark-corenlp

    This package wraps Stanford CoreNLP annotators ...

  • Keras-ResNeXt

    Keras ResNeXt Implementation of ResNeXt models...

  • capsnet-with-caps...

    CapsNet with capsule-wise convolution Project ...

  • inferno-boilerplate

    This is a very basic boilerplate example for pe...