mlsanityData to 7 Oct 2026

MatConvNet - Convolutional Neural Networks for MATLAB

arXiv 1412.4564 ↗First posted 15 Dec 2014cs.CV cs.LG cs.MScited by 36

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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.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Dec 2014.

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Citing papers per year: 2019: 1; 2020: 0; 2021: 12; 2022: 8; 2023: 7; 2024: 4; 2025: 2; 2026: 2.

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  1. 2021Segmentation of Shoulder Muscle MRI Using a New Region and Edge based Deep Auto-Encodercited by 15
  2. 2023Tensor Decomposition for Model Reduction in Neural Networks: A Reviewcited by 14
  3. 2021SPOT: A framework for selection of prototypes using optimal transportcited by 13
  4. 2022COVID-19 Detection and Analysis From Lung CT Images using Novel Channel Boosted CNNscited by 12
  5. 2022Siamese Object Tracking for Unmanned Aerial Vehicle: A Review and Comprehensive Analysiscited by 11
  6. 2021Teacher-Student Training and Triplet Loss to Reduce the Effect of Drastic Face Occlusioncited by 9
  7. 2022Deep Learning Methods for Fingerprint-Based Indoor Positioning: A Reviewcited by 8
  8. 2022Vision-based Human Fall Detection Systems using Deep Learning: A Reviewcited by 7
  9. 2025Catch-Only-One: Non-Transferable Examples for Model-Specific Authorizationcited by 7
  10. 2019Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behaviorcited by 6
  11. 2021Generalized Tensor Summation Compressive Sensing Network (GTSNET): An Easy to Learn Compressive Sensing Operationcited by 4
  12. 2021VisGraphNet: a complex network interpretation of convolutional neural featurescited by 4
24 more
  1. 2022CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for Energy-Efficient Low-precision Deep Convolutional Neural Networkscited by 4
  2. 2022Iris super-resolution using CNNs: is photo-realism important to iris recognition?cited by 4
  3. 2021Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantizationcited by 3
  4. 2024In Defense and Revival of Bayesian Filtering for Thermal Infrared Object Trackingcited by 3
  5. 2021Semi-Supervised Metric Learning: A Deep Resurrectioncited by 2
  6. 2023Design and Implementation of A Soccer Ball Detection System with Multiple Camerascited by 2
  7. 2021A Deep Learning-Based Unified Framework for Red Lesions Detection on Retinal Fundus Imagescited by 1
  8. 2024Improving Generalization of Deep Neural Networks by Optimum Shiftingcited by 1
  9. 2024Feature Selection Based on Wasserstein Distancecited by 1
  10. 2021Cellcounter: a deep learning framework for high-fidelity spatial localization of neuronscited by 0
  11. 2021Training Deep Neural Networks via Branch-and-Boundcited by 0
  12. 2021Convolutional Neural Networks in Orthodontics: a reviewcited by 0
  13. 2021Morphological Classification of Galaxies in S-PLUS using an Ensemble of Convolutional Networkscited by 0
  14. 2022Scale Invariant Semantic Segmentation with RGB-D Fusioncited by 0
  15. 2022Combined Learning of Neural Network Weights for Privacy in Collaborative Taskscited by 0
  16. 2023Large-scale Global Low-rank Optimization for Computational Compressed Imagingcited by 0
  17. 2023Unsupervised ore/waste classification on open-cut mine faces using close-range hyperspectral datacited by 0
  18. 2023A Light-Weight Contrastive Approach for Aligning Human Pose Sequencescited by 0
  19. 2023The challenge of representation learning: Improved accuracy in deep vision models does not come with better predictions of perceptual similaritycited by 0
  20. 2023APRF: Anti-Aliasing Projection Representation Field for Inverse Problem in Imagingcited by 0
  21. 2024Learning to Adapt Category Consistent Meta-Feature of CLIP for Few-Shot Classificationcited by 0
  22. 2025Exploring Diffusion with Test-Time Training on Efficient Image Restorationcited by 0
  23. 2026Real-Time Human Detection for Aerial Captured Video Sequences via Deep Modelscited by 0
  24. 2026SSPFormer: Self-Supervised Pretrained Transformer for MRI Imagescited by 0