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Jinjia Zhou and Jian Yang
Compressive Sensing (CS) has emerged as a transformative technique in image compression, offering innovative solutions to challenges in efficient signal representation and acquisition. This paper provides a comprehensive exploration of the key components...
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Yousef Abbaspour-Gilandeh, Abdollah Aghabara, Mahdi Davari and Joe Mari Maja
There are many methods to detect plant pests and diseases, but they are primarily time-consuming and costly. Computer vision techniques can recognize the pest- and disease-damaged fruits and provide clues to identify and treat the diseases and pests in t...
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Kaizhuang Yan, Yongxian Wang and Wenbin Xiao
The sound speed profile data of seawater provide an important basis for carrying out underwater acoustic modeling and analysis, sonar performance evaluation, and underwater acoustic assistant decision-making. The data volume of the high-resolution sound ...
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Duo Teng, Yatian Li, Hu Yang, Zhiqiang Wei and Yaan Li
Underwater acoustic imaging employs a special form of array which includes numerous transducer elements to achieve beamforming. Although a large-scale array can bring high imaging resolution, it will also cause difficulties in hardware complexity and rea...
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Xianghua Tan, Yushi Sun, Weili Zeng and Zhibin Quan
The air traffic control sector (ATCS) is the basic unit of the airspace system. If we can identify the congestion of an ATCS, it will help provide decision support for planning and daily operations. However, current methods mainly characterize congestion...
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Jongsu Yoon and Yoonsik Choe
Retinex theory represents the human visual system by showing the relative reflectance of an object under various illumination conditions. A feature of this human visual system is color constancy, and the Retinex theory is designed in consideration of thi...
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Rui Ding, Shunming Li, Jiantao Lu, Kun Xu and Jinrui Wang
In recent years, the method of deep learning has been widely used in the field of fault diagnosis of mechanical equipment due to its strong feature extraction and other advantages such as high efficiency, portability, and so on. However, at present, most...
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Nikolaos Kilis and Nikolaos Mitianoudis
This paper presents a novel scheme for speech dereverberation. The core of our method is a two-stage single-channel speech enhancement scheme. Degraded speech obtains a sparser representation of the linear prediction residual in the first stage of our pr...
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Yaoxian Liu, Yi Sun and Bin Li
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Sangkyun Lee and Jeonghyun Lee
Deep neural networks (DNNs) have been quite successful in solving many complex learning problems. However, DNNs tend to have a large number of learning parameters, leading to a large memory and computation requirement. In this paper, we propose a model c...
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