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Jian Liu, Shihui Yu, Xuemei Liu, Guohang Lu, Zhenbo Xin and Jin Yuan
In-field in situ droplet deposition digitization is beneficial for obtaining feedback on spraying performance and precise spray control, the cost-effectiveness of the measurement system is crucial to its scalable application. However, the limitations of ...
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Napsu Karmitsa, Sona Taheri, Kaisa Joki, Pauliina Paasivirta, Adil M. Bagirov and Marko M. Mäkelä
In this paper, a new nonsmooth optimization-based algorithm for solving large-scale regression problems is introduced. The regression problem is modeled as fully-connected feedforward neural networks with one hidden layer, piecewise linear activation, an...
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Pir Dino Soomro, Xianping Fu, Muhammad Aslam, Dani Elias Mfungo and Arsalan Ali
An imperative application of artificial intelligence (AI) techniques is visual object detection, and the methods of visual object detection available currently need highly equipped datasets preserved in a centralized unit. This usually results in high tr...
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Gaoyuan Cai, Juhu Li, Xuanxin Liu, Zhibo Chen and Haiyan Zhang
Recently, the deep neural network (DNN) has become one of the most advanced and powerful methods used in classification tasks. However, the cost of DNN models is sometimes considerable due to the huge sets of parameters. Therefore, it is necessary to com...
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Binghang Lu, Christian Moya and Guang Lin
This paper presents NSGA-PINN, a multi-objective optimization framework for the effective training of physics-informed neural networks (PINNs). The proposed framework uses the non-dominated sorting genetic algorithm (NSGA-II) to enable traditional stocha...
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Dexi Zhan, Yongqi Mu, Wenxu Duan, Mingzhu Ye, Yingqiang Song, Zhenqi Song, Kaizhong Yao, Dengkuo Sun and Ziqi Ding
Soil water content is an important indicator used to maintain the ecological balance of farmland. The efficient spatial prediction of soil water content is crucial for ensuring crop growth and food production. To this end, 104 farmland soil samples were ...
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Xinze Yang, Chunkai Zhang, Yizhi Sun, Kairui Pang, Luru Jing, Shiyun Wa and Chunli Lv
This research primarily explores the application of Natural Language Processing (NLP) technology in precision financial fraud detection, with a particular focus on the implementation and optimization of the FinChain-BERT model. Firstly, the FinChain-BERT...
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Jong-Wook Kim, Jin-Young Choi, Eun-Ju Ha and Jae-Ho Choi
Seniors who live alone at home are at risk of falling and injuring themselves and, thus, may need a mobile robot that monitors and recognizes their poses automatically. Even though deep learning methods are actively evolving in this area, they have limit...
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Yankai Lv, Haiyan Ding, Hao Wu, Yiji Zhao and Lei Zhang
Federated learning (FL) is an emerging decentralized machine learning framework enabling private global model training by collaboratively leveraging local client data without transferring it centrally. Unlike traditional distributed optimization, FL trai...
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Qing Zhao, Honglei Wei and Xianyi Zhai
The proposed method for tire specification character recognition based on the YOLOv5 network aimed to address the low efficiency and accuracy of the current character recognition methods. The approach involved making three major modifications to the YOLO...
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