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End-to-end dilated convolution network for document image semantic segmentation

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0 Published in 2021 at "Journal of Central South University"

DOI: 10.1007/s11771-021-4731-9

Abstract: Semantic segmentation is a crucial step for document understanding. In this paper, an NVIDIA Jetson Nano-based platform is applied for implementing semantic segmentation for teaching artificial intelligence concepts and programming. To extract semantic structures from… read more here.

Keywords: network; end; dilated convolution; segmentation ... See more keywords

EHDC: enhanced dilated convolution framework for underwater blurred target recognition

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1 Published in 2022 at "Robotica"

DOI: 10.1017/s0263574722001059

Abstract: Abstract The autonomous underwater vehicle (AUV) has a problem with feature loss when recognizing small targets underwater. At present, algorithms usually use multi-scale feature extraction to solve the problem, but this method increases the computational… read more here.

Keywords: recognition; dilated convolution; underwater; underwater blurred ... See more keywords

Transformable Dilated Convolution by Distance for LiDAR Semantic Segmentation

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1 Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3225556

Abstract: LiDAR semantic segmentation is essential in autonomous vehicle safety. A rotating 3D LiDAR projects more laser points onto nearby objects and fewer points onto farther objects. Therefore, when projecting points onto a 2D image, such… read more here.

Keywords: dilated convolution; receptive field; distance; lidar ... See more keywords

Fusing Attention Network Based on Dilated Convolution for Superresolution

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1 Published in 2023 at "IEEE Transactions on Cognitive and Developmental Systems"

DOI: 10.1109/tcds.2022.3153090

Abstract: Deep neural networks with different filters or multiple branches have achieved good performance for single superresolution (SR) in recent years. However, they ignore the high-frequency components of the multiscale context information of the low-resolution image.… read more here.

Keywords: dilated convolution; network based; attention network; fusing attention ... See more keywords

A Novel Multichannel Dilated Convolution Neural Network for Human Activity Recognition

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0 Published in 2020 at "Mathematical Problems in Engineering"

DOI: 10.1155/2020/5426532

Abstract: A novel multichannel dilated convolution neural network for improving the accuracy of human activity recognition is proposed. The proposed model utilizes the multichannel convolution structure with multiple kernels of various sizes to extract multiscale features… read more here.

Keywords: dilated convolution; convolution; human activity; activity recognition ... See more keywords

Detecting Asymptomatic Infections of Rice Bacterial Leaf Blight Using Hyperspectral Imaging and 3-Dimensional Convolutional Neural Network With Spectral Dilated Convolution

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1 Published in 2022 at "Frontiers in Plant Science"

DOI: 10.3389/fpls.2022.963170

Abstract: Rice is one of the most important food crops for human beings. Its total production ranks third in the grain crop output. Bacterial Leaf Blight (BLB), as one of the three major diseases of rice,… read more here.

Keywords: spectral dilated; bacterial leaf; dilated convolution; leaf blight ... See more keywords

Contour Detection for Fibre of Preserved Szechuan Pickle Based on Dilated Convolution

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1 Published in 2019 at "Applied Sciences"

DOI: 10.3390/app9132684

Abstract: Peeling fibre is an indispensable process in the production of preserved Szechuan pickle, the accuracy of which can significantly influence the quality of the products, and thus the contour method of fibre detection, as a… read more here.

Keywords: preserved szechuan; szechuan pickle; contour; fibre ... See more keywords

Hybrid Dilated Convolution with Multi-Scale Residual Fusion Network for Hyperspectral Image Classification

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0 Published in 2021 at "Micromachines"

DOI: 10.3390/mi12050545

Abstract: The convolutional neural network (CNN) has been proven to have better performance in hyperspectral image (HSI) classification than traditional methods. Traditional CNN on hyperspectral image classification is used to pay more attention to spectral features… read more here.

Keywords: network; hybrid dilated; dilated convolution; hyperspectral image ... See more keywords