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VoxelMatters5h
Sparc3D introduces next-gen high-resolution 3D model generation
Explore how Sparc3D transforms 2D images into detailed 3D models with AI-powered efficiency and precision. Discover more.
Scientific Research Publishing2mon
Sun, Y., Xue, B., Zhang, M. and Yen, G.G. (2019) A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification. IEEE Transactions on Neural ...
The encoder and decoder are composed of convolutional layer ... that this method can effectively integrate the channel attention module and the fully convolutional autoencoder. Although it is an ...
Scientific Research Publishing3mon
A Combination Method of Stacked Convolutional Auto-Encoder and Selective Kernel Attention Mechanism for Image Classification ()
The encoder and decoder are composed of convolutional layer ... that this method can effectively integrate the channel attention module and the fully convolutional autoencoder. Although it is an ...
IEEE1y
Elimination of Random Mixed Noise in ECG Using Convolutional Denoising Autoencoder With Transformer Encoder
To suppress random mixed noise (RMN) in ECG with less distortion, we propose a Transformer-based Convolutional Denoising AutoEncoder model (TCDAE) in this study. The encoder of TCDAE is composed of ...
Frontiers1y
A blind convolutional deep autoencoder for spectral unmixing of hyperspectral images over waterbodies
We propose a convolutional autoencoder, where the encoder performs the convolutional operations, and the ASC constraint is applied based on the customization of a regularization layer during the ...
GitHub2y
convolutional-autoencoder
This project is a practice implementation of an autoencoder, The primary use case for this autoencoder is for anomaly detection in sales data, but it can be adapted for other purposes. The autoencoder ...