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Chun-Myoung Noh, Jun-Gyo Jang, Sung-Soo Kim, Soon-Sup Lee, Sung-Chul Shin and Jae-Chul Lee
With increasing interest in smart factories, considerable attention has been paid to the development of deep-learning-based quality inspection systems. Deep-learning-based quality inspection helps productivity improvements by solving the limitations of e...
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Subin Kim, Heejin Hwang, Keunyeong Oh and Jiuk Shin
The seismically deficient column details in existing reinforced concrete buildings affect the overall behavior of the building depending on the failure type of the column. The purpose of this study is to develop and validate a machine-learning-based pred...
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Munir Ahmad, Sagheer Abbas, Areej Fatima, Ghassan F. Issa, Taher M. Ghazal and Muhammad Adnan Khan
The importance of accurate livestock identification for the success of modern livestock industries cannot be overstated as it is essential for a variety of purposes, including the traceability of animals for food safety, disease control, the prevention o...
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Fei Wu, Yitao Zhang, Lang Wang, Qiu Hu, Shengli Fan and Weiming Cai
The species and population size of marine fish are important for maintaining the ecological environment and reflecting climate change. Traditional fish detection methods mainly rely on manual or traditional computer vision, which has disadvantages such a...
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Chunhua Zhu, Jiarui Liang and Fei Zhou
Stemming from the overlap of objects and undertraining due to few samples, road dense object detection is confronted with poor object identification performance and the inability to recognize edge objects. Based on this, one transfer learning-based YOLOv...
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Muhamad Jumaa, Mohammed Saqib, Arif Attar
Pág. 85 - 92
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Cesar Davila Hernandez, Jungseok Ho, Dongchul Kim and Abdoul Oubeidillah
During every Atlantic hurricane season, storms represent a constant risk to Texan coastal communities and other communities along the Atlantic coast of the United States. A storm surge refers to the abnormal rise of sea water level due to hurricanes and ...
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Francisco Andree Ramírez Casas, Laxmi Sushama and Bernardo Teufel
The development of a computationally efficient machine learning-based framework to understand the underlying causes for biases in climate model simulated fields is presented in this study. The framework consists of a two-step approach, with the first ste...
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Xiaolong Tang, Changjie Wu and Xiaoyan Xu
The steering mechanism of ship steering gear is generally driven by a hydraulic system. The precise control of the hydraulic cylinder in the steering mechanism can be achieved by the target rudder angle. However, hydraulic systems are often described as ...
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Enna Hirata and Takuma Matsuda
With the increasing availability of large datasets and improvements in prediction algorithms, machine-learning-based techniques, particularly deep learning algorithms, are becoming increasingly popular. However, deep-learning algorithms have not been wid...
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Jianjun Ni, Yan Chen, Yu Gu, Xiaolong Fang and Pengfei Shi
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Jeong-Myeong Choi, Yoon-Kyoung Lee, Jong-Dae Kim, Chan-Young Park and Yu-Seop Kim
To assess a child?s language development, utterance data are required. The approach of recording and transcribing the conversation between the expert and the child is mostly utilized to obtain utterance data. Because data are obtained through one-on-one ...
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Tiansheng Miao, He Huang, Jiayuan Guo, Guanghua Li, Yu Zhang and Naijia Chen
Seawater intrusion is expected to cause a shortage of freshwater resources in coastal areas which will hinder regional economic and social development. The consequences of global climate change include rising sea levels, which also affect the results of ...
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Hari Wahjono, Bambang Budi Wiyono, Maisyaroh and Mustiningsih
This study aims to describe the implementation of online learning that is applied today, and to develop a blended learning model as a strategy to provide student services according to the diversity of potential, needs, interests, and learning speeds. Thi...
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Liyang Wang, Gaurav Misra and Xiaoli Bai
Wind speed estimation for rotary-wing vertical take-off and landing (VTOL) UAVs is challenging due to the low accuracy of airspeed sensors, which can be severely affected by the rotor?s down-wash effect. Unlike traditional aerodynamic modeling solutions,...
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Javensius Sembiring, Rianto Adhy Sasongko, Eduardo I. Bastian, Bayu Aji Raditya and Rayhan Ekananto Limansubroto
This paper investigates the development of a deep learning-based flight control model for a tilt-rotor unmanned aerial vehicle, focusing on altitude, speed, and roll hold systems. Training data is gathered from the X-Plane flight simulator, employing a p...
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Hang Zhou, Weicong Li, Ziqi Jiang, Fanger Cai and Yuting Xue
Accurate flight departure time prediction enables the rational use of airport support resources, aprons, and runway resources, and promotes the implementation of collaborative decision-making. In order to accurately predict the flight departure time, thi...
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Minghao Liu, Jianxiang Wang, Qingxi Luo, Lingbo Sun and Enming Wang
Exploring spatial anisotropy features and capturing spatial interactions during urban change simulation is of great significance to enhance the effectiveness of dynamic urban modeling and improve simulation accuracy. Addressing the inadequacies of curren...
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Xuejun Yue, Haifeng Li, Qingkui Song, Fanguo Zeng, Jianyu Zheng, Ziyu Ding, Gaobi Kang, Yulin Cai, Yongda Lin, Xiaowan Xu and Chaoran Yu
Existing disease detection models for deep learning-based monitoring and prevention of pepper diseases face challenges in accurately identifying and preventing diseases due to inter-crop occlusion and various complex backgrounds. To address this issue, w...
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Efrem Yohannes Obsie, Hongchun Qu, Yong-Jiang Zhang, Seanna Annis and Francis Drummond
Early detection and accurately rating the level of plant diseases plays an important role in protecting crop quality and yield. The traditional method of mummy berry disease (causal agent: Monilinia vaccinii-corymbosi) identification is mainly based on f...
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