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 …
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
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 …
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
Fire is one of the most frequent and common emergencies threatening public safety and
social development. Recently, intelligent fire detection technologies represented by …
social development. Recently, intelligent fire detection technologies represented by …
Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images
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 …
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
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 …
development throughout history, with the agricultural sector playing a pivotal role. Insufficient …
Deep adaptive wavelet network
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 …
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 …
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 …
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 …
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 …
input images. Although it reduces the computation requirements into a reasonable range …