MatConvNet
MatConvNet is a MATLAB toolbox designed for implementing Convolutional Neural Networks (CNNs) tailored for computer vision tasks. It offers a streamlined approach to run and train advanced CNN architectures, featuring numerous pre-trained models for image classification, segmentation, face recognition, and text detection. The latest updates enhance modularity, support for CuDNN, and various utility functions.
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Top MatConvNet Features
- Modular system for contributions
- Support for recent CuDNN versions
- Efficient C++ codebase
- Pre-trained CNNs available
- Image classification capabilities
- Segmentation functionality
- Face recognition support
- Text detection features
- Extensive example library
- Utility functions included
- Cross-platform compatibility
- Detailed documentation provided
- Integration with VLFeat library
- Fast-RCNN demo implementation
- Easy MATLAB interface
- Support for large-scale SVM training
- Local features extraction algorithms
- Superpixel segmentation algorithms
- Bugfixes in recent updates
- Community-driven enhancements.
