News
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results