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Feifei He, Qinjuan Wan, Yongqiang Wang, Jiang Wu, Xiaoqi Zhang and Yu Feng
Accurately predicting hydrological runoff is crucial for water resource allocation and power station scheduling. However, there is no perfect model that can accurately predict future runoff. In this paper, a daily runoff prediction method with a seasonal...
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Siyu Qi, Minxue He, Raymond Hoang, Yu Zhou, Peyman Namadi, Bradley Tom, Prabhjot Sandhu, Zhaojun Bai, Francis Chung, Zhi Ding, Jamie Anderson, Dong Min Roh and Vincent Huynh
Salinity management in estuarine systems is crucial for developing effective water-management strategies to maintain compliance and understand the impact of salt intrusion on water quality and availability. Understanding the temporal and spatial variatio...
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Xinyu Jia, Xueqin Jiang, Zhiyong Li, Jiong Mu, Yuchao Wang and Yupeng Niu
The occurrence of pests at high frequencies has been identified as a major cause of reduced citrus yields, and early detection and prevention are of great significance to pest control. At present, studies related to citrus pest identification using deep ...
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Qiqi Zheng, Chao Wei, Xinfei Yan, Housong Ruan and Bangyu Wu
Seismic elastic parameter inversion translates seismic data into subsurface structures and physical properties of formations. Traditional model-based inversion methods have limitations in retrieving complex geological structures. In recent years, deep le...
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Eran Shachar, Israel Cohen and Baruch Berdugo
This paper presents an echo suppression system that combines a linear acoustic echo canceller (AEC) with a deep complex convolutional recurrent network (DCCRN) for residual echo suppression. The filter taps of the AEC are adjusted in subbands by using th...
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Marcia L. Baptista and Helmut Prendinger
Prognostics and health management is an engineering discipline that aims to support system operation while ensuring maximum safety and performance. Prognostics is a key step of this framework, focusing on developing effective maintenance policies based o...
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Yiqi Wu, Mei Liu, Zhaoyuan Peng, Meiqi Liu, Miao Wang and Yingqi Peng
Cattle behaviour is a significant indicator of cattle welfare. With the advancements in electronic equipment, monitoring and classifying multiple cattle behaviour patterns is becoming increasingly important in precision livestock management. The aim of t...
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Guillaume Coiffier, Ghouthi Boukli Hacene and Vincent Gripon
Deep Neural Networks are state-of-the-art in a large number of challenges in machine learning. However, to reach the best performance they require a huge pool of parameters. Indeed, typical deep convolutional architectures present an increasing number of...
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Yen-Cheng Chu, Yun-Jie Jhang, Tsung-Ming Tai and Wen-Jyi Hwang
The objective of this study is to present novel neural network (NN) algorithms and systems for sensor-based hand gesture recognition. The algorithms are able to classify accurately a sequence of hand gestures from the sensory data produced by acceleromet...
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Tessfu Geteye Fantaye, Junqing Yu and Tulu Tilahun Hailu
Deep neural networks (DNNs) have shown a great achievement in acoustic modeling for speech recognition task. Of these networks, convolutional neural network (CNN) is an effective network for representing the local properties of the speech formants. Howev...
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