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Behnam Faghih and Joseph Timoney
Some of the applications of this study are singing and notes alignment, singing and lyrics alignment, singing analysis, voice analysis, singing assessment, singing information retrieval, evaluating pitch detection algorithms, evaluating note extraction a...
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Ahram Song and Yongil Kim
Although semantic segmentation of remote-sensing (RS) images using deep-learning networks has demonstrated its effectiveness recently, compared with natural-image datasets, obtaining RS images under the same conditions to construct data labels is difficu...
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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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Ahram Song
Deep learning techniques have recently shown remarkable efficacy in the semantic segmentation of natural and remote sensing (RS) images. However, these techniques heavily rely on the size of the training data, and obtaining large RS imagery datasets is d...
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Alberto del Rio, Giuseppe Conti, Sandra Castano-Solis, Javier Serrano, David Jimenez and Jesus Fraile-Ardanuy
The digital transition that drives the new industrial revolution is largely driven by the application of intelligence and data. This boost leads to an increase in energy consumption, much of it associated with computing in data centers. This fact clashes...
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Roberta Vrskova, Robert Hudec, Patrik Kamencay and Peter Sykora
Interest in utilizing neural networks in a variety of scientific and academic studies and in industrial applications is increasing. In addition to the growing interest in neural networks, there is also a rising interest in video classification. Object de...
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Xi He, Heng Dong, Wanli Yang and Jun Hong
Mounting concerns pertaining to energy efficiency have led to the research of load monitoring. By Non-Intrusive Load Monitoring (NILM), detailed information regarding the electric energy consumed by each appliance per day or per hour can be formed. The a...
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Moussa Diallo, Shengwu Xiong, Eshete Derb Emiru, Awet Fesseha, Aminu Onimisi Abdulsalami and Mohamed Abd Elaziz
Classification algorithms have shown exceptional prediction results in the supervised learning area. These classification algorithms are not always efficient when it comes to real-life datasets due to class distributions. As a result, datasets for real-l...
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Vijayakumar Varadarajan, Dweepna Garg and Ketan Kotecha
Deep learning is a relatively new branch of machine learning in which computers are taught to recognize patterns in massive volumes of data. It primarily describes learning at various levels of representation, which aids in understanding data that includ...
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Nisim Hurst-Tarrab, Leonardo Chang, Miguel Gonzalez-Mendoza and Neil Hernandez-Gress
Parking block regions host dangerous behaviors that can be detected from a surveillance camera perspective. However, these regions are often occluded, subject to ground bumpiness or steep slopes, and thus they are hard to segment. Firstly, the paper prop...
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Mohamed Soliman, Mohamed M. Morsy and Hany G. Radwan
Floods are one of the most dangerous water-related risks. Numerous sources of uncertainty affect flood modeling. High-resolution land-cover maps along with appropriate Manning?s roughness values are the most significant parameters for building an accurat...
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Nuha Alruwais and Mohammed Zakariah
The process of learning about a student?s knowledge and comprehension of a particular subject is referred to as student knowledge assessment. It helps to identify areas where students need additional support or challenge and can be used to evaluate the e...
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Takuo Higashide, Katsuyuki Tanaka, Takuji Kinkyo and Shigeyuki Hamori
This study analyzes the importance of the Tokyo Stock Exchange Co-Location dataset (TSE Co-Location dataset) to forecast the realized volatility (RV) of Tokyo stock price index futures. The heterogeneous autoregressive (HAR) model is a popular linear reg...
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Moses Lesiba Gadebe,Okuthe Paul Kogeda
Pág. pp. 68 - 86
The availability of Smartphones has increased the possibility of self-monitoring to increase physical activity and behavior change to prevent obesity. However self-monitoring on a Smartphtone comes with some challenges such as unavailability of lightweig...
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Guobiao Yao, Jin Zhang, Jianya Gong and Fengxiang Jin
To promote the development of deep learning for feature matching, image registration, and three-dimensional reconstruction, we propose a method of constructing a deep learning benchmark dataset for affine-invariant feature matching. Existing images often...
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Dongbo Zhou, Shuangjian Liu, Jie Yu and Hao Li
The existing remote sensing image datasets target the identification of objects, features, or man-made targets but lack the ability to provide the date and spatial information for the same feature in the time-series images. The spatial and temporal infor...
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Athita Onuean, Uraiwan Buatoom, Thatsanee Charoenporn, Taehong Kim and Hanmin Jung
In handwriting recognition research, a public image dataset is necessary to evaluate algorithm correctness and runtime performance. Unfortunately, in existing Thai language script image datasets, there is a lack of variety of standard handwriting types. ...
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Haitao Zhang, Huixian Shen, Kang Ji, Rui Song, Jinyuan Liu and Yuxin Yang
Applying spatial clustering algorithms on large-scale spatial interactive dataset to find urban hot/cold spots is a new idea to assist urban management. However, the research usually focuses on the dataset with spatio-temporal proximity, rather than remo...
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Rongke Wei, Anyang Song, Huixian Duan and Haodong Pei
With the development of space technology, deep learning methods, with their excellent generalization ability, are increasingly applied in various space activities. The space object data is difficult to obtain, which greatly limits its application in spac...
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Zaira Hassan Amur, Yew Kwang Hooi, Gul Muhammad Soomro, Hina Bhanbhro, Said Karyem and Najamudin Sohu
Keyword extraction is a critical task that enables various applications, including text classification, sentiment analysis, and information retrieval. However, the lack of a suitable dataset for semantic analysis of keyword extraction remains a serious p...
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