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Jianyuan Li, Xiaochun Lu, Ping Zhang and Qingquan Li
The timely identification and detection of surface cracks in concrete dams, an important public safety infrastructure, is of great significance in predicting engineering hazards and ensuring dam safety. Due to their low efficiency and accuracy, manual de...
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Jinna Shi, Wenxiu Zhang and Yanru Zhao
In order to improve the prediction accuracy of the machine learning model for concrete fatigue life using small datasets, a group calculation and random weight dynamic time warping barycentric averaging (GRW-DBA) data augmentation method is proposed. Fir...
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Yiheng Zhou, Kainan Ma, Qian Sun, Zhaoyuxuan Wang and Ming Liu
Over the past several decades, deep neural networks have been extensively applied to medical image segmentation tasks, achieving significant success. However, the effectiveness of traditional deep segmentation networks is substantially limited by the sma...
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Andressa C. M. da Silveira, Álvaro Sobrinho, Leandro Dias da Silva, Evandro de Barros Costa, Maria Eliete Pinheiro and Angelo Perkusich
Chronic kidney disease (CKD) is a worldwide public health problem, usually diagnosed in the late stages of the disease. To alleviate such issue, investment in early prediction is necessary. The purpose of this study is to assist the early prediction of C...
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Cesar Federico Caiafa, Jordi Solé-Casals, Pere Marti-Puig, Sun Zhe and Toshihisa Tanaka
In many machine learning applications, measurements are sometimes incomplete or noisy resulting in missing features. In other cases, and for different reasons, the datasets are originally small, and therefore, more data samples are required to derive use...
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Tomislav Malvic, Josip Iv?inovic, Josipa Velic and Rajna Rajic
The interpolation of small datasets is challenging problem regarding the selection of interpolation methods and type of datasets. Here, for such analysis, the analysed data was taken in two hydrocarbon fields (?A? and ?B?), located in the western part of...
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Mahmoud Maher ElMorshedy, Radwa Fathalla and Yasser El-Sonbaty
Compactness and separability of data points are two important properties that contribute to the accuracy of machine learning tasks such as classification and clustering. We propose a framework that enhances the goodness criteria of the two properties by ...
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Ala Hijazi, Sameer Al-Dahidi and Safwan Altarazi
An artificial neural network (ANN) extracts knowledge from a training dataset and uses this acquired knowledge to forecast outputs for any new set of inputs. When the input/output relations are complex and highly non-linear, the ANN needs a relatively la...
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Jinlong Wang, Dong Cui and Qiang Zhang
With sentiment prediction technology, businesses can quickly look at user reviews to find ways to improve their products and services. We present the BertBilstm Multiple Emotion Judgment (BBMEJ) model for small-sample emotion prediction tasks to solve th...
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Marius Paraschiv, Ricardo Padrino, Paolo Casari, Eyal Bigal, Aviad Scheinin, Dan Tchernov and Antonio Fernández Anta
The automatic classification of fish species appearing in images and videos from underwater cameras is a challenging task, albeit one with a large potential impact in environment conservation, marine fauna health assessment, and fishing policy. Deep neur...
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Jaekyung Kim, Jungwoo Huh, Ingu Park, Junhyeong Bak, Donggeon Kim and Sanghoon Lee
Deep learning-based object detection is one of the most popular research topics. However, in cases where large-scale datasets are unavailable, the training of detection models remains challenging due to the data-driven characteristics of deep learning. S...
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Nguyen Trung Tuan, Philip Moore, Dat Ha Vu Thanh and Hai Van Pham
ChatGPT plays significant roles in the third decade of the 21st Century. Smart cities applications can be integrated with ChatGPT in various fields. This research proposes an approach for developing large language models using generative artificial intel...
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Mohammad Wedyan, Alessandro Crippa and Adel Al-Jumaily
Deep neural networks are successful learning tools for building nonlinear models. However, a robust deep learning-based classification model needs a large dataset. Indeed, these models are often unstable when they use small datasets. To solve this issue,...
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Cong Xu, Justin Morgenroth and Bruce Manley
In New Zealand, approximately 70% of plantation forests are large-scale (over 1000 ha) with accurate resource description. In contrast, the remaining 30% of plantation forests are small-scale (less than 1000 ha). It is forecasted that these small-scale f...
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Mia MacTavish, Lakin Wecker and Faramarz Samavati
The use of perspective projection in data visualization has been shown to potentially aid with the perception of small values in datasets with important variations at multiple scales. We integrate perspective charts, which use perspective projection in t...
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Junjie Liu, Yong Yang, Xiaochao Fan, Ge Ren, Liang Yang and Qian Ning
The rapid identification of offensive language in social media is of great significance for preventing viral spread and reducing the spread of malicious information, such as cyberbullying and content related to self-harm. In existing research, the public...
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Yule Chen, Hong Liang and Shuo Pang
Underwater target classification methods based on deep learning suffer from obvious model overfitting and low recognition accuracy in the case of small samples and complex underwater environments. This paper proposes a novel classification network (Effic...
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Darian M. Onchis, Flavia Costi, Codruta Istin, Ciprian Cosmin Secasan and Gabriel V. Cozma
(1) Background: Lung cancers are the most common cancers worldwide, and prostate cancers are among the second in terms of the frequency of cancers diagnosed in men. Automatic ranking of the risk groups of such diseases is highly in demand, but the clinic...
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Alex Brisbois and Rebecca Dziedzic
Installing pumps as turbines (PaTs) in water distribution networks can recover otherwise wasted energy, as well as reduce leakage caused by high water pressure. However, a barrier to their implementation is the lack of information on their performance in...
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Suleiman Abahussein, Dayong Ye, Congcong Zhu, Zishuo Cheng, Umer Siddique and Sheng Shen
Online food delivery services today are considered an essential service that gets significant attention worldwide. Many companies and individuals are involved in this field as it offers good income and numerous jobs to the community. In this research, we...
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