# MatConvNet - Convolutional Neural Networks for MATLAB

arXiv: https://arxiv.org/abs/1412.4564 · HTML: https://mlsanity.com/paper/1412.4564/

## Key facts

- Cited by 36 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Dec 2014.

## Built on by (most cited first, 30 of 36)

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- [Teacher-Student Training and Triplet Loss to Reduce the Effect of Drastic Face Occlusion](https://mlsanity.com/paper/2111.10561/) (2021)
- [Deep Learning Methods for Fingerprint-Based Indoor Positioning: A Review](https://mlsanity.com/paper/2205.14935/) (2022)
- [Vision-based Human Fall Detection Systems using Deep Learning: A Review](https://mlsanity.com/paper/2207.10952/) (2022)
- [Catch-Only-One: Non-Transferable Examples for Model-Specific Authorization](https://mlsanity.com/paper/2510.10982/) (2025)
- [Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior](https://mlsanity.com/paper/1910.11703/) (2019)
- [Generalized Tensor Summation Compressive Sensing Network (GTSNET): An Easy to Learn Compressive Sensing Operation](https://mlsanity.com/paper/2108.03167/) (2021)
- [VisGraphNet: a complex network interpretation of convolutional neural features](https://mlsanity.com/paper/2108.12490/) (2021)
- [CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for Energy-Efficient Low-precision Deep Convolutional Neural Networks](https://mlsanity.com/paper/2208.00331/) (2022)
- [Iris super-resolution using CNNs: is photo-realism important to iris recognition?](https://mlsanity.com/paper/2210.13125/) (2022)
- [Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization](https://mlsanity.com/paper/2110.12478/) (2021)
- [In Defense and Revival of Bayesian Filtering for Thermal Infrared Object Tracking](https://mlsanity.com/paper/2402.17098/) (2024)
- [Semi-Supervised Metric Learning: A Deep Resurrection](https://mlsanity.com/paper/2105.05061/) (2021)
- [Design and Implementation of A Soccer Ball Detection System with Multiple Cameras](https://mlsanity.com/paper/2302.00123/) (2023)
- [A Deep Learning-Based Unified Framework for Red Lesions Detection on Retinal Fundus Images](https://mlsanity.com/paper/2109.05021/) (2021)
- [Improving Generalization of Deep Neural Networks by Optimum Shifting](https://mlsanity.com/paper/2405.14111/) (2024)
- [Feature Selection Based on Wasserstein Distance](https://mlsanity.com/paper/2411.07217/) (2024)
- [Cellcounter: a deep learning framework for high-fidelity spatial localization of neurons](https://mlsanity.com/paper/2103.10462/) (2021)
- [Training Deep Neural Networks via Branch-and-Bound](https://mlsanity.com/paper/2104.01730/) (2021)
- [Convolutional Neural Networks in Orthodontics: a review](https://mlsanity.com/paper/2104.08886/) (2021)
- [Morphological Classification of Galaxies in S-PLUS using an Ensemble of Convolutional Networks](https://mlsanity.com/paper/2107.02287/) (2021)
- [Scale Invariant Semantic Segmentation with RGB-D Fusion](https://mlsanity.com/paper/2204.04679/) (2022)
- [Combined Learning of Neural Network Weights for Privacy in Collaborative Tasks](https://mlsanity.com/paper/2205.00361/) (2022)
- [Large-scale Global Low-rank Optimization for Computational Compressed Imaging](https://mlsanity.com/paper/2301.03047/) (2023)
- [Unsupervised ore/waste classification on open-cut mine faces using close-range hyperspectral data](https://mlsanity.com/paper/2302.04936/) (2023)
- [A Light-Weight Contrastive Approach for Aligning Human Pose Sequences](https://mlsanity.com/paper/2303.04244/) (2023)

## Abstract (arXiv)

MatConvNet is an implementation of Convolutional Neural Networks (CNNs) for MATLAB. 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 linear convolutions with filter banks, feature pooling, and many more. In this manner, MatConvNet allows 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. This document provides an overview of CNNs and how they are implemented in MatConvNet and gives the technical details of each computational block in the toolbox.