Andrea Vedaldi
ABSTRACT
MatConvNet is an open source implementation of Convolutional Neural Networks (CNNs) with a deep integration in the MATLAB environment. The toolbox is designed with an emphasis on simplicity and flexibility. It exposes the building blocks of CNNs as easy-to-use MATLAB functions, providing routines for computing convolutions with filter banks, feature pooling, normalisation, and much more. MatConvNet can be easily extended, often using only MATLAB code, allowing fast prototyping of new CNN architectures. At the same time, it supports efficient computation on CPU and GPU, allowing to train complex models on large datasets such as ImageNet ILSVRC containing millions of training examples
- K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman. Return of the devil in the details: Delving deep into convolutional nets. In Proc. BMVC, 2014.Google Scholar
Cross Ref
- J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. ImageNet: A Large-Scale Hierarchical Image Database. In Proc. CVPR, 2009.Google ScholarCross Ref
- S. Ioffe and C. Szegedy. Batch normalization: Accelerating deep network training by reducing internal covariate shift. CoRR, 2015.Google Scholar
- A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In Proc. NIPS, 2012.Google ScholarDigital Library
- M. Lin, Q. Chen, and S. Yan. Network in network. CoRR, abs/1312.4400, 2013.Google Scholar
- K. Simonyan, A. Vedaldi, and A. Zisserman. Deep inside convolutional networks: Visualising image classification models and saliency maps. In Proc. ICLR, 2014.Google Scholar
- K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. CoRR, abs/1409.1556, 2014.Google Scholar
- A. Vedaldi and B. Fulkerson. VLFeat -- An open and portable library of computer vision algorithms. In Proc. ACM Int. Conf. on Multimedia, 2010. Google ScholarDigital Library
Index Terms
- MatConvNet: Convolutional Neural Networks for MATLAB
Recommendations
LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning
MM '16: Proceedings of the 24th ACM international conference on MultimediaLightNet is a lightweight, versatile, purely Matlab-based deep learning framework. The idea underlying its design is to provide an easy-to-understand, easy-to-use and efficient computational platform for deep learning research. The implemented framework ...
MatConvNet: CNNs are also for MATLAB users
MatConvNet is an open source MATLAB toolbox implementing Convolutional Neural Networks (CNNs) for computer vision and multimedia applications, developed by the same authors of the famed VLFeat library. Both libraries have associated papers that have ...
On the performance evaluation of object classification models in low altitude aerial data
AbstractThis paper compares the classification performance of machine learning classifiers vs. deep learning-based handcrafted models and various pretrained deep networks. The proposed study performs a comprehensive analysis of object classification ...
Comments