Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multi-phase flow in heterogeneous random media . uncertainty-quantification time-dependent multi-phase-flows ...

We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder ...

In order to address these challenges, we propose a convolutional encoder-decoder model with deep learning for document image binarization in this paper. In the proposed method, mid-level document ...

The Convolutional encoder and Viterbi decoder are implemented using Verilog HDL and the code has been developed under full-custom design. This implementation is complicated when using Verilog HDL ...

Convolutional codes represent a cornerstone in modern communications, offering a method for continuously encoding data streams to mitigate errors due to interference and noise. These codes operate ...

In this paper, a modified FPGA scheme for the convolutional encoder and Viterbi decoder based on the IEEE 802.11a standards of WLAN is presented in OFDM baseband processing systems. The proposed ...