Ling Zhou

Orcid: 0009-0008-8592-3870

Affiliations:
  • Henan Institute of Science and Technology, Institute of Computer Applications, School of Information Engineering, Xinxiang, China


According to our database1, Ling Zhou authored at least 14 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Bibliography

2025
AGANet: Attention-Guided Generative Adversarial Network for Corn Hyperspectral Images Augmentation.
IEEE Trans. Consumer Electron., May, 2025

Underwater image color correction via global and local two-step optimization.
Pattern Recognit. Lett., 2025

2024
Underwater Image Enhancement via Weighted Wavelet Visual Perception Fusion.
IEEE Trans. Circuits Syst. Video Technol., April, 2024

Local Reference Feature Transfer (LRFT): A simple pre-processing step for image enhancement.
Pattern Recognit. Lett., 2024

Image dehazing using non-local haze-lines and multi-exposure fusion.
J. Vis. Commun. Image Represent., 2024

CATNet: Cascaded attention transformer network for marine species image classification.
Expert Syst. Appl., 2024

DBANet: Dual-branch Attention Network for hyperspectral remote sensing image classification.
Comput. Electr. Eng., 2024

2023
Underwater image enhancement via complementary advantage fusion of global and local contrast.
Comput. Electr. Eng., December, 2023

CSKNN: Cost-sensitive K-Nearest Neighbor using hyperspectral imaging for identification of wheat varieties.
Comput. Electr. Eng., October, 2023

Tensor based low rank representation of hyperspectral images for wheat seeds varieties identification.
Comput. Electr. Eng., September, 2023

MCANet: Multi-channel attention network with multi-color space encoder for underwater image classification.
Comput. Electr. Eng., May, 2023

Feature selection and cascade dimensionality reduction for self-supervised visual representation learning.
Comput. Electr. Eng., March, 2023

DAMNet: Dual Attention Mechanism Deep Neural Network for Underwater Biological Image Classification.
IEEE Access, 2023

2022
Multi-feature embedded learning SVM for cloud detection in remote sensing images.
Comput. Electr. Eng., 2022


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