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Diya Wang, Yonglin Zhang, Lixin Wu, Yupeng Tai, Haibin Wang, Jun Wang, Fabrice Meriaudeau and Fan Yang
In recent years, the study of deep learning techniques for underwater acoustic channel estimation has gained widespread attention. However, existing neural network channel estimation methods often overfit to training dataset noise levels, leading to dimi...
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Roopdeep Kaur, Gour Karmakar and Muhammad Imran
In digital image processing, filtering noise is an important step for reconstructing a high-quality image for further processing such as object segmentation, object detection, and object recognition. Various image-denoising approaches, including median, ...
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Teresa Kwamboka Abuya, Richard Maina Rimiru and George Onyango Okeyo
Denoising computed tomography (CT) medical images is crucial in preserving information and restoring images contaminated with noise. Standard filters have extensively been used for noise removal and fine details? preservation. During the transmission of ...
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Congyu Jiao, Fanjie Meng, Tingxuan Li and Ying Cao
Single image deraining (SID) has shown its importance in many advanced computer vision tasks. Although many CNN-based image deraining methods have been proposed, how to effectively remove raindrops while maintaining background structure remains a challen...
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Qi Liu, Peng Nie, Hualin Dai, Liyuan Ning and Jiaxing Wang
Convolutional neural networks (CNN) are widely used for structural damage identification. However, the presence of environmental disturbances introduces noise into the acquired acceleration response data, impairing the performance of CNN models. In this ...
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Wan Teng Tey, Tee Connie, Kan Yeep Choo and Michael Kah Ong Goh
Traditional methods used to identify and monitor insect species are time-consuming, costly, and fully dependent on the observer?s ability. This paper presents a deep learning-based cicada species recognition system using acoustic signals to classify the ...
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Junbin Zang, Juliang Wang, Zhidong Zhang, Yongqiu Zheng and Chenyang Xue
Cardiovascular disease and its consequences on human health have never stopped and even show a trend of appearing in increasingly younger generations. The establishment of an excellent deep learning algorithm model to assist physicians in identifying and...
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Subhrajit Dey, Rajdeep Bhattacharya, Friedhelm Schwenker and Ram Sarkar
Image denoising is a challenging research problem that aims to recover noise-free images from those that are contaminated with noise. In this paper, we focus on the denoising of images that are contaminated with additive white Gaussian noise. For this pu...
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