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Xuanzhi Liao, Shahnorbanun Sahran, Azizi Abdullah and Syaimak Abdul Shukor
Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their prob...
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Hilmy Assodiky, Iwan Syarif, Tessy Badriyah
Pág. 75 - 91
Arrhythmia is a heartbeat abnormality that can be harmless or harmful. It depends on what kind of arrhythmia that the patient suffers. People with arrhythmia usually feel the same physical symptoms but every arrhythmia requires different treatments. For ...
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Sheng Zhang, Guangzhong Liu and Chen Cheng
Over the past few decades, unmanned surface vehicles (USV) have drawn a lot of attention. But because of the wind, waves, currents, and other sporadic disturbances, it is challenging to understand and collect correct data about USV dynamics. In this pape...
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Chengyin Ru, Shihai Zhang, Chongnian Qu and Zimiao Zhang
Aiming at the application of the overhead transmission line insulator patrol inspection requirements based on the unmanned aerial vehicle (UAV), a lightweight ECA-YOLOX-Tiny model is proposed by embedding the efficient channel attention (ECA) module into...
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Abu Bakar, Ke Li, Haobo Liu, Ziqi Xu, Marco Alessandrini and Dongsheng Wen
The airfoil is the prime component of flying vehicles. For low-speed flights, low Reynolds number airfoils are used. The characteristic of low Reynolds number airfoils is a laminar separation bubble and an associated drag rise. This paper presents a fram...
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Gokhan Gungor and Mehdi Afshari
In this study, a sensorimotor controller is designed to characterize the required muscle force to enable a robotics system to perform a human-like circular movement. When the appropriate muscle internal forces are chosen, the arm end-point tracks the des...
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Yu Yao and Quan Qian
We develop the online process parameter design (OPPD) framework for efficiently handling streaming data collected from industrial automation equipment. This framework integrates online machine learning, concept drift detection and Bayesian optimization t...
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Yuting Guan, Junjiang He, Tao Li, Hui Zhao and Baoqiang Ma
SQL injection is a highly detrimental web attack technique that can result in significant data leakage and compromise system integrity. To counteract the harm caused by such attacks, researchers have devoted much attention to the examination of SQL injec...
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Yunhe Guo, Zijian Jiang, Hanqiao Huang, Hongjia Fan and Weiye Weng
In order to improve the problem of overly relying on situational information, high computational power requirements, and weak adaptability of traditional maneuver methods used by hypersonic vehicles (HV), an intelligent maneuver strategy combining deep r...
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Ruichen Zhang, Shaofeng Bian and Houpu Li
The digital elevation model (DEM) is known as one kind of the most significant fundamental geographical data models. The theory, method and application of DEM are hot research issues in geography, especially in geomorphology, hydrology, soil and other re...
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Jinghan Wang, Guangyue Li and Wenzhao Zhang
The powerful performance of deep learning is evident to all. With the deepening of research, neural networks have become more complex and not easily generalized to resource-constrained devices. The emergence of a series of model compression algorithms ma...
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Shun-Chieh Hsieh
The need for accurate tourism demand forecasting is widely recognized. The unreliability of traditional methods makes tourism demand forecasting still challenging. Using deep learning approaches, this study aims to adapt Long Short-Term Memory (LSTM), Bi...
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Jegalakshimi Jewaratnam
Pág. 31
A multilayer feedforward neural network (MFNN) model is developed from the best performing backpropagation training algorithm among all eleven training algorithms. From experimental setup of microwave pyrolysis of oil palm fibre, the model utilized the i...
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Dongfei Xue, Xiaonian Wang, Jin Zhu, Darryl N. Davis, Bing Wang, Wenbing Zhao, Yonghong Peng and Yongqiang Cheng
Some machine learning algorithms have shown a better overall recognition rate for facial recognition than humans, provided that the models are trained with massive image databases of human faces. However, it is still a challenge to use existing algorithm...
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Jingsha He, Qi Xiao, Peng He and Muhammad Salman Pathan
In recent years, smart home technologies have started to be widely used, bringing a great deal of convenience to people?s daily lives. At the same time, privacy issues have become particularly prominent. Traditional encryption methods can no longer meet ...
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Jingsha He, Qi Xiao, Peng He and Muhammad Salman Pathan
In recent years, smart home technologies have started to be widely used, bringing a great deal of convenience to people?s daily lives. At the same time, privacy issues have become particularly prominent. Traditional encryption methods can no longer meet ...
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Jin Wang, Peng Zhao, Zhe Zhang, Ting Yue, Hailiang Liu and Lixin Wang
The upset state is an unexpected flight state, which is characterized by an unintentional deviation from normal operating parameters. It is difficult for the pilot to recover the aircraft from the upset state accurately and quickly. In this paper, an ups...
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Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner...
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Yizhuo Zhang, Hantao Liu, Xingyu Liu and Huiling Yu
Due to the complex structure of high-canopy-density forests, the traditional individual tree segmentation (ITS) algorithms based on ALS point cloud, which set segmentation threshold manually, is difficult to adequately cover a variety of complex situatio...
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Cheng Zhu, Shaoqi Wang, Na He, Hui Sun, Linjuan Xu and Filip Gurkalo
To improve the accuracy of debris flow forecasts and serve as disaster prevention and mitigation, an accurate and intelligent early warning method of debris flow initiation based on the IGWO-LSTM algorithm is proposed. First, the entropy method is employ...
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