This paper discusses the trade-off problem between network capacity and performance for the image de-snowing task.

The combination of dual recursive strategy and DC-LSTM significantly improves snow removal performance while restoring better texture details to the images.

This paper aims to address the above problem by making a trade-off between network capacity and performance. We propose two novel networks suitable for ...

Lightweight image de-snowing: A better trade-off between network capacity and performance · Zheng Chen, Yiwen Sun, +1 author. Jianyu Yue · Published in Neural ...

Neural Networks · Archive · Vol. 165, No. C. Volume 165, Issue CAug ... Lightweight image de-snowing: A better trade-off between network capacity and performance.

Lightweight image de-snowing: A better trade-off between network capacity and performance · Chen, Zheng; Sun, Yiwen; Bi, Xiaojun; Yue, Jianyu.

Omni-scale feature learning for lightweight image dehazing · Lightweight image de-snowing: A better trade-off between network capacity and performance. Citing ...

Lightweight image de-snowing: A better trade-off between network capacity and performance · Computer Science. Neural Networks · 2023.

Lightweight image de-snowing: A better trade-off between network capacity and performance. August 01, 2023. [ MEDLINE Abstract ]. Stereoscopic scalable ...

It unifies downsampling with wavelet transform to losslessly decompress feature maps, providing an efficient trade-off between performance and computation. Ref.