Nov 25, 2022 · Lightweight real-time semantic segmentation requires a neural network that perfectly balances segmentation accuracy and parameter quantity.
Dec 15, 2022 · This paper proposes a lightweight multi-dimensional dynamic convolutional network (LMDCNet) for real-time semantic segmentation to address this problem.
This paper proposes a lightweight multi-dimensional dynamic convolutional network (LMDCNet) for real-time semantic segmentation to address this problem. At the ...
Abstract: Semantic segmentation can address the perceived needs of autonomous driving and micro-robots and is one of the challenging tasks in computer ...
A Lightweight and Dynamic Convolutional Network for Real ...
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In this paper, semantic segmentation network for detecting walls of indoor scenes is presented. Given an image of an indoor scene, the network automatically ...
This paper introduces a lightweight convolutional neural network, called FDDWNet, for real-time accurate semantic segmentation, which makes an effort to ...
The standard for evaluating the quality of a lightweight real-time semantic segmentation network is that the higher the accuracy, the lower the parameters, and ...
In this work, a novel semantic segmentation network is introduced, which integrates the strengths of Convolutional Neural Networks and Transformer mechanisms ...
We propose a lightweight real-time semantic segmentation network called LETNet. LETNet combines a U-shaped CNN with Transformer effectively in a capsule ...
Jun 29, 2023 · The proposed DLS-Net has fewer parameters but achieves similar accuracy to U-net++, helps CAD algorithm achieve higher accuracy, which facilitates wider ...