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You Sheng Toh and Carol Anne Hargreaves
Extensive medical research has revealed evidence of a strong association between hippocampus atrophy and age-related diseases such as Alzheimer?s disease (AD). Therefore; segmentation of the hippocampus is an important task that can help clinicians and r...
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Jocelyn Sabatier and Christophe Farges
This paper proposes algorithms to model fractional (dynamical) behaviors using non-singular rational kernels whose interest is first demonstrated on a pure power law function. Two algorithms are then proposed to find a non-singular rational kernel that a...
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Jinnan Wang, Weiqin Tong and Xiaoli Zhi
Convolutional neural networks (CNNs) have made impressive achievements in image classification and object detection. For hardware with limited resources, it is not easy to achieve CNN inference with a large number of parameters without external storage. ...
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Ziyi Li, Yang Li, Yanping Wang, Guangda Xie, Hongquan Qu and Zhuoyang Lyu
With the rapid development of deep learning, more and more complex models are applied to 3D point cloud object detection to improve accuracy. In general, the more complex the model, the better the performance and the greater the computational resource co...
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Hua Yang, Shuxiang Zhang, Hao Shen, Gexiang Zhang, Xingquan Deng, Jianglin Xiong, Li Feng, Junxiong Wang, Haifeng Zhang and Shenyang Sheng
Text classification is one of the fundamental tasks in natural language processing and is widely applied in various domains. CNN effectively utilizes local features, while the Attention mechanism performs well in capturing content-based global interactio...
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Xin-Yi Yuan, Yue Hua, Nadine Aubry, Mansur Zhussupbekov, James F. Antaki, Zhi-Fu Zhou and Jiang-Zhou Peng
This study develops a data-driven reduced-order model based on a deep convolutional neural network (CNN) for real-time and accurate prediction of the drug trajectory and concentration field in transarterial chemoembolization therapy to assist in directin...
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Thanh-Dat Truong, Chi Nhan Duong, Minh-Triet Tran, Ngan Le and Khoa Luu
Flow-based generative models have recently become one of the most efficient approaches to model data generation. Indeed, they are constructed with a sequence of invertible and tractable transformations. Glow first introduced a simple type of generative f...
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Romain Lecuyer-Le Bris, Marc Le Boulluec, Jean-Frédéric Charpentier and Mohamed Benbouzid
This paper focuses on the formulation of state?space representations of radiation forces for marine structures using Hankel Singular Value Decomposition (HSVD), a method used to obtain a state?space realization from a Hankel matrix, with the classical de...
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Art J. R. Pelling and Ennes Sarradj
State-space models have been successfully employed for model order reduction and control purposes in acoustics in the past. However, due to the cubic complexity of the singular value decomposition, which makes up the core of many subspace system identifi...
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Yingying Wang, Yibin Li, Yong Song and Xuewen Rong
The convolutional neural network (CNN) has been widely used in image recognition field due to its good performance. This paper proposes a facial expression recognition method based on the CNN model. Regarding the complexity of the hierarchic structure of...
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Samuel Bansah, Samuel Ato Andam-Akorful, Jonathan Quaye-Ballard, Matthew Coffie Wilson, Solomon Senyo Gidigasu and Geophrey K. Anornu
Using d18O and d2H in mean transit time (MTT) modeling can ensure the verifiability of results across catchments. The main objectives of this study were to (i) evaluate the d18O- and d2H-based behavioral transit time distributions and (ii) assess if d18O...
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Mehdi Ghoreyshi, Ivan Greisz, Adam Jirasek and Matthew Satchell
The stresses resulting from wind gusts can exceed the limit value and may cause large-scale structural deformation or even failure. All certified airplanes should therefore withstand the increased loads from gusts of considerable intensity. A large facto...
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Weiwei Zhang, Xin Ma, Yuzhao Zhang, Ming Ji and Chenghui Zhen
Due to the arbitrariness of the drone?s shooting angle of view and camera movement and the limited computing power of the drone platform, pedestrian detection in the drone scene poses a greater challenge. This paper proposes a new convolutional neural ne...
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Jinkai Guo, Xiao Xiao, Jianchi Miao, Bingquan Tian, Jing Zhao and Yubin Lan
In order to achieve accurate detection of mature Zanthoxylum in their natural environment, a Zanthoxylum detection network based on the YOLOv5 object detection model was proposed. It addresses the issues of irregular shape and occlusion caused by the gro...
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Juanli Jing, Menglin Zhai, Shiqing Dou, Lin Wang, Binghai Lou, Jichi Yan and Shixin Yuan
The accurate identification of citrus fruits is important for fruit yield estimation in complex citrus orchards. In this study, the YOLOv7-tiny-BVP network is constructed based on the YOLOv7-tiny network, with citrus fruits as the research object. This n...
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Jiapeng Cui and Feng Tan
Rice diseases are extremely harmful to rice growth, and achieving the identification and rapid classification of rice disease spots is an essential means to promote intelligent rice production. However, due to the large variety of rice diseases and the s...
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Yongjiu Zou, Jinqiu Zhang, Taili Du, Xingjia Jiang, Hao Wang, Peng Zhang, Yuewen Zhang and Peiting Sun
According to statistics, about 70% of ship fire accidents occur in the engine room, due to the complex internal structure and various combustible materials. Once a fire occurs, it is difficult to extinguish and significantly impacts the crew?s life and p...
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Shengnan Hao, Haotian Wu, Yanyan Jiang, Zhanlin Ji, Li Zhao, Linyun Liu and Ivan Ganchev
Accurate segmentation of lesions can provide strong evidence for early skin cancer diagnosis by doctors, enabling timely treatment of patients and effectively reducing cancer mortality rates. In recent years, some deep learning models have utilized compl...
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Yuntao Shi, Qi Luo, Meng Zhou, Wei Guo, Jie Li, Shuqin Li and Yu Ding
Objects thrown from tall buildings in communities are characterized by their small size, inconspicuous features, and high speed. Existing algorithms for detecting such objects face challenges, including excessive parameters, overly complex models that ar...
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Wen Tian, Yining Zhang, Ying Zhang, Haiyan Chen and Weidong Liu
To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study was co...
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