Call it the return of Clippy — this time with AI. Microsoft’s new small language model shows us the future of interfaces.

Next-generation U-Net Encoder: Decoder for accurate, automated CTC detection from images of peripheral blood nucleated cells stained with EPCAM and DAPI.. If you have the appropriate software ...

Deep-learning-based watermarking technique is being extensively studied. Most existing approaches adopt a similar encoder-driven scheme which we name END (Encoder-NoiseLayer-Decoder) architecture. In ...

In this paper, we have proposed an effective stacked convolutional auto-encoder that integrates a selective kernel attention mechanism for image classification. This model is based on a fully ...

Discover the power of sparse autoencoders in machine learning. Our in-depth article explores how these neural networks compress and reconstruct data, extract meaningful features, and enhance the ...

To carry out cell counting, it is common to use neural network models with an encoder-decoder structure to generate regression density maps. In the encoder-decoder structure, skip connections are ...

An Encoder-decoder architecture in machine learning efficiently translates one sequence data form to another.

The auto-encoder in the model replaces the coding and modulation part of the traditional communication system, while the auto-decoder replaces the traditional communication system decoding and ...