Results 51 to 60 of about 306 (168)

Image Fusion using Non Subsampled Contourlet Transform in Medical Field

International Journal of Engineering and Advanced Technology, 2020
Image fusion is a powerful method and developing field in the area of image processing. The image fusion is a type of methodology that combines the two or more images into single more informative image. Image fusion is the process of assimilation of numerous input images into a new single fused image with highly informative than the input image.
Jampani Ravi,, M. Gowri Sri Durga, Y. D. R. Ch. Kartheek, MD. Shabeena Begum, T. Raju, T. V. Syamala Raju   +5 more
openaire   +2 more sources

AI safety of film capacitors

IET Nanodielectrics, Volume 7, Issue 3, Page 131-139, September 2024.
i) Unlike before, with film capacitors as a specific target, we raise concerns about the possible safety risks posed by AI. The breadth of application of AI in film capacitors is shown by review and summary, and this is also the range of potential threats.
Yong‐Xin Zhang, Fang‐Yi Chen, Di‐Fan Liu, Jian‐Xiao Wang, Qi‐Kun Feng, Hai‐Yang Jiang, Xin‐Jie Wang, Hong‐Bo Zhao, Shao‐Long Zhong, Faisal Mehmood Shah, Zhi‐Min Dang   +10 more
wiley   +1 more source

Non-Subsampled Contourlet Transform-Based Domain Feedback Information Distillation Network for Suppressing Noise in Seismic Data

Applied Sciences
Seismic signal processing often relies on general convolutional neural network (CNN)-based models, which typically focus on features in the time domain while neglecting frequency characteristics. Moreover, down-sampling operations in these models tend to
Kang Chen, Guangzhi Zhang, Cong Tang, Qi Ran, Long Wen, Song Han, Han Liang, Haiyong Yi   +7 more
doaj   +1 more source

Underwater image clarifying based on human visual colour constancy using double‐opponency

CAAI Transactions on Intelligence Technology, Volume 9, Issue 3, Page 632-648, June 2024.
Abstract Underwater images are often with biased colours and reduced contrast because of the absorption and scattering effects when light propagates in water. Such images with degradation cannot meet the needs of underwater operations. The main problem in classic underwater image restoration or enhancement methods is that they consume long calculation ...
Bin Kong, Jing Qian, Pinhao Song, Jing Yang, Amir Hussain   +4 more
wiley   +1 more source

An infrared and visible image fusion network based on multi‐scale feature cascades and non‐local attention

IET Image Processing, Volume 18, Issue 8, Page 2114-2125, 19 June 2024.
This paper introduces a novel infrared and visible image fusion network to address the limitations of auto‐encoder fusion networks. In the designed network, the encoder employs a multi‐branch cascade structure with convolution kernels of different sizes to extract multi‐scale features, and the fusion layer incorporates a non‐local attention module ...
Jing Xu, Zhenjin Liu, Ming Fang
wiley   +1 more source

An adaptive neuro‐fuzzy inference system optimized by genetic algorithm for brain tumour detection in magnetic resonance images

IET Image Processing, Volume 18, Issue 5, Page 1358-1372, 17 April 2024.
An adaptive neuro‐fuzzy inference system is presented based on an optimization of genetic algorithm to classify normal and abnormal brain tumours. Abstract An adaptive neuro‐fuzzy inference system is presented which is optimized by a genetic algorithm to classify normal and abnormal brain tumours.
Marzieh Ghahramani, Nabiollah Shiri
wiley   +1 more source

Deep learning applications in protein crystallography

Acta Crystallographica Section A, Volume 80, Issue 1, Page 1-17, January 2024.
Deep learning applications are increasingly dominating many areas of science. This paper reviews their relevance for and impact on protein crystallography.Deep learning techniques can recognize complex patterns in noisy, multidimensional data. In recent years, researchers have started to explore the potential of deep learning in the field of structural
Senik Matinyan, Pavel Filipcik, Jan Pieter Abrahams   +2 more
wiley   +1 more source

Infrared and visible image fusion using NSCT-HRCNN: a training-free feature extraction approach

Complex & Intelligent Systems
Infrared and visible images capture distinct environmental features that image fusion can integrate into a single, information-rich representation. Traditional fusion algorithms often struggle with low precision, color distortion, and detail loss, while ...
Haoran Liu, Yiran Chen, Peng Li, Mingzhe Liu, Haihua Ding, Mingrong Xiang, Shihao Zhao, Peiran Dai   +7 more
doaj   +1 more source

A Novel Infrared and Visible Image Information Fusion Method Based on Phase Congruency and Image Entropy

Entropy, 2019
In multi-modality image fusion, source image decomposition, such as multi-scale transform (MST), is a necessary step and also widely used. However, when MST is directly used to decompose source images into high- and low-frequency components, the ...
Xinghua Huang, Guanqiu Qi, Hongyan Wei, Yi Chai, Jaesung Sim   +4 more
doaj   +1 more source

Sparse Regularization Based on Orthogonal Tensor Dictionary Learning for Inverse Problems

Mathematical Problems in Engineering, Volume 2024, Issue 1, 2024.
In seismic data processing, data recovery including reconstruction of the missing trace and removal of noise from the recorded data are the key steps in improving the signal‐to‐noise ratio (SNR). The reconstruction of seismic data and removal of noise becomes a sparse optimization problem that can be solved by using sparse regularization.
Diriba Gemechu, Francisco Rossomando
wiley   +1 more source