All snow removed: Single image desnowing algorithm using hierarchical dual-tree complex wavelet representation and contradict channel loss

WT Chen, HY Fang, CL Hsieh… - Proceedings of the …, 2021 - openaccess.thecvf.com
Snow is a highly complicated atmospheric phenomenon that usually contains snowflake,
snow streak, and veiling effect (similar to the haze or the mist). In this literature, we propose …

Rice diseases detection and classification using attention based neural network and bayesian optimization

Y Wang, H Wang, Z Peng - Expert Systems with Applications, 2021 - Elsevier
In this research, an attention-based depthwise separable neural network with Bayesian
optimization (ADSNN-BO) is proposed to detect and classify rice disease from rice leaf …

Fire detection in video surveillances using convolutional neural networks and wavelet transform

L Huang, G Liu, Y Wang, H Yuan, T Chen - Engineering Applications of …, 2022 - Elsevier
Fire is one of the most frequent and common emergencies threatening public safety and
social development. Recently, intelligent fire detection technologies represented by …

Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images

M Yahyatabar, P Jouvet… - 2020 42nd Annual …, 2020 - ieeexplore.ieee.org
Automatic and accurate lung segmentation in chest X-ray (CXR) images is fundamental for
computer-aided diagnosis systems since the lung is the region of interest in many diseases …

Using a Resnet50 with a kernel attention mechanism for rice disease diagnosis

MSAM Al-Gaashani, NA Samee, R Alnashwan… - Life, 2023 - mdpi.com
The domestication of animals and the cultivation of crops have been essential to human
development throughout history, with the agricultural sector playing a pivotal role. Insufficient …

Deep adaptive wavelet network

MXB Rodriguez, A Gruson, L Polania… - Proceedings of the …, 2020 - openaccess.thecvf.com
Even though convolutional neural networks have become the method of choice in many
fields of computer vision, they still lack interpretability and are usually designed manually in …

DMCNN: a deep multiscale convolutional neural network model for medical image segmentation

L Teng, H Li, S Karim - Journal of Healthcare Engineering, 2019 - Wiley Online Library
Medical image segmentation is one of the hot issues in the related area of image
processing. Precise segmentation for medical images is a vital guarantee for follow‐up …

Combining max-pooling and wavelet pooling strategies for semantic image segmentation

A de Souza Brito, MB Vieira, MLSC De Andrade… - Expert Systems with …, 2021 - Elsevier
This paper presents a novel multi-pooling architecture generated by combining the
advantages of wavelet and max-pooling operations in convolutional neural networks …

Study on MRI medical image segmentation technology based on CNN-CRF model

N Feng, X Geng, L Qin - IEEE Access, 2020 - ieeexplore.ieee.org
Image segmentation is an important technique for segmenting images without overlap**
each other and having their own features. It has been rapidly developed in the field of …

Image classification using convolutional neural network with wavelet domain inputs

L Wang, Y Sun - IET Image Processing, 2022 - Wiley Online Library
Commonly used convolutional neural networks (CNNs) usually compress high‐resolution
input images. Although it reduces the computation requirements into a reasonable range …