MatConvNet: CNNs are also for MATLAB users - Vedaldi, A; Lux, M; Bertini, M (Association for Computing Machinery, 2018)
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 been presented within the Open Source Software Competition track of ACM Multimedia: "MatConvNet: Convolutional Neural Networks for MATLAB" [1] and "Vlfeat: an open and portable library of computer vision algorithms" [2]. At present, the MatConvNet paper is the second most cited ACM Multimedia paper, according to Google Scholar. The pros of this toolbox is its simplicity, thanks to the integration with MATLAB environment, efficiency thanks to the use of GPUs and CuDNN libraries, and the fact that it can run and learn state-of-the-art CNNs. After all it has been developed by the same people that brought VGG-16 and VGG-19 CNNs... Many pre-trained CNNs for image classification (e.g. ResNet), segmentation, face recognition (e.g. VGG Face), object (e.g. Fast-R CNN) and text detection (e.g. VGG Text) are available in the model zoo.