Add a description, image, and links to the convolutional-encoder-decoder topic page so that developers can more easily learn about it.

Abstract: In this paper, we consider the design of the Tail-Biting Convolutional Code Decoder (TB-CCD) for the Long Term Evolution (LTE) system. Tail-biting convolutional coding is used for channel ...

A simple yet powerful Morse Code encoder built in Assembly (MASM), converting alphanumeric input into dots and dashes using a memory-based lookup table. It demonstrates the enduring relevance of Morse ...

Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant improvements in classification accuracy. However, most current hyperspectral ...

Digital tools and non-destructive monitoring techniques are crucial for real-time evaluations of crop output and health in sustainable agriculture, particularly for precise above-ground biomass (AGB) ...

In this tutorial, we explore a novel deep learning approach that combines multi-head latent attention with fine-grained expert segmentation. By harnessing the power of latent attention, the model ...

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...

1 College of Information Engineering, Xinchuang Software Industry Base, Yancheng Teachers University, Yancheng, China. 2 Yancheng Agricultural College, Yancheng, China. Convolutional auto-encoders ...