1D convolutional neural networks and applications: A survey

🤖 Plain-English Summary

During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. The benchmark datasets and the principal 1D CNN software used in those applications are also publicly shared in a dedicated website.

🔑 Key Findings

• CNNs are feed-forward Artificial Neural Networks (ANNs) with alternating convolutional and subsampling layers.
• Deep 2D CNNs with many hidden layers and millions of parameters have the ability to learn complex objects and patterns providing that they can be trained on a massive size visual database with ground-truth labels.
• With a proper training, this unique ability makes them the primary tool for various engineering applications for 2D signals such as images and video frames.

🔗 Related Resources