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A-optimal convolutional neural network

Neural Computing and Applications, 2016
In this paper, we propose a novel data representation-classification model learning algorithm. The model is a convolutional neural network (CNN), and we learn its parameters to achieve A-optimality. The input multi-instance data are represented by a CNN model, and then classified by a linear classification model.
Zihong Yin   +5 more
openaire   +1 more source

Quadtree Convolutional Neural Networks

2018
This paper presents a Quadtree Convolutional Neural Network (QCNN) for efficiently learning from image datasets representing sparse data such as handwriting, pen strokes, freehand sketches, etc. Instead of storing the sparse sketches in regular dense tensors, our method decomposes and represents the image as a linear quadtree that is only refined in ...
Pradeep Kumar Jayaraman   +3 more
openaire   +1 more source

A Survey on Convolution Neural Networks

2020 IEEE REGION 10 CONFERENCE (TENCON), 2020
Major tools to implement any Artificial Intelligence and Machine Learning systems are Symbolic AI and Artificial Neural Network (ANN) AI. ANN has made a dramatic improvement in the versatile area of Machine Learning (ML). ANN is a gathering of vast number of weighted interconnected artificial neurons, initially invented with the inspiration of ...
openaire   +1 more source

Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks

ACM Computing Surveys, 2022
Claudio Filipi Goncalves dos Santos   +1 more
exaly  

A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects

IEEE Transactions on Neural Networks and Learning Systems, 2022
Jun Zhou, Fan Liu, Zewen Li
exaly  

1D Convolutional Neural Networks and Applications: A Survey

Mechanical Systems and Signal Processing, 2021
Daniel J. Inman   +2 more
exaly  

EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks

IEEE Transactions on Affective Computing, 2020
Zhen Cui, Peng Song, Wenming Zheng
exaly  

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