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Obada Issa and Tamer Shanableh
This paper proposes a novel approach to activity recognition where videos are compressed using video coding to generate feature vectors based on compression variables. We propose to eliminate the temporal domain of feature vectors by computing the mean a...
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Ivana Marin, Sa?a Mladenovic, Sven Gotovac and Goran Zaharija
The global community has recognized an increasing amount of pollutants entering oceans and other water bodies as a severe environmental, economic, and social issue. In addition to prevention, one of the key measures in addressing marine pollution is the ...
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Taufik Fuadi Abidin, Amir Mahazir, Muhammad Subianto, Khairul Munadi and Ridha Ferdhiana
During the previous decades, intelligent identification of acronym and expansion pairs from a large corpus has garnered considerable research attention, particularly in the fields of text mining, entity extraction, and information retrieval. Herein, we p...
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Mrinmoy Sarkar, Dhiman Chowdhury, Celia Shahnaz and Shaikh Anowarul Fattah
Electrical network frequency (ENF) is a signature of a power distribution grid. It represents the deviation from the nominal frequency (50 or 60 Hz) of a power system network. The variations in ENF sequences within a grid are subject to load fluctuations...
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Su Yang and Farzin Deravi
In this paper, a novel re-engineering mechanism for the generation of word embeddings is proposed for document-level sentiment analysis. Current approaches to sentiment analysis often integrate feature engineering with classification, without optimizing ...
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Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna and James Y. Zou
Interpretability is becoming an active research topic as machine learning (ML) models are more widely used to make critical decisions. Tabular data are one of the most commonly used modes of data in diverse applications such as healthcare and finance. Mu...
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Wei-Wei Jin, Guo-Hong Chen, Zhuo Chen, Yun-Lei Sun, Jie Ni, Hao Huang, Wai-Hung Ip and Kai-Leung Yung
In this work, we propose a road pavement damage detection deep learning model based on feature points from a local minimum of grayscale. First, image blocks, consisting of the neighborhood of feature points, are cut from the image window to form an image...
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Hye-Jin Lee, Yongjin Kwon and Sun-Young Ihm
In this paper, we propose the duality-based image sequence matching method, which is called Dual-ISM, a subsequence matching method for searching for similar images. We first extract feature points from the given image data and configure the feature vect...
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Houaria ABED, Lynda ZAOUI
Pág. 97 - 113
Recent years have witnessed great interest in developing methods for content-based image retrieval (CBIR). Generally, the image search results which are returned by an image search engine contain multiple topics, and organizing the results into different...
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Yuanzhi Pan, Hua Jin, Jiechao Gao and Hafiz Tayyab Rauf
The livestock of Pakistan includes different animal breeds utilized for milk farming and exporting worldwide. Buffalo have a high milk production rate, and Pakistan is the third-largest milk-producing country, and its production is increasing over time. ...
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Chulseung Yang, Gi Won Ku, Jeong-Gi Lee and Sang-Hyun Lee
This paper presents an interval-based LDA (Linear Discriminant Analysis) algorithm for individual verification using ECG (Electrocardiogram). In this algorithm, at first, unwanted noise and power-line interference are removed from the ECG signal. Then, t...
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Yinsheng Chen, Tinghao Zhang, Zhongming Luo and Kun Sun
To improve the fault identification accuracy of rolling bearing and effectively analyze the fault severity, a novel rolling bearing fault diagnosis and severity analysis method based on the fast sample entropy, the wavelet packet energy entropy, and a mu...
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Yinsheng Chen, Tinghao Zhang, Wenjie Zhao, Zhongming Luo and Kun Sun
A rolling bearing is an important connecting part between rotating machines. It is susceptible to mechanical stress and wear, which affect the running state of bearings. In order to effectively identify the fault types and analyze the fault severity of r...
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Jingchao Jiang, Junzhi Liu, Cheng-Zhi Qin and Dongliang Wang
Urban flood control requires real-time and spatially detailed information regarding the waterlogging depth over large areas, but such information cannot be effectively obtained by the existing methods. Video supervision equipment, which is readily availa...
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Vrushang Patel, Sheela Ramanna, Ketan Kotecha and Rahee Walambe
Text classification aims to assign labels to textual units such as documents, sentences and paragraphs. Some applications of text classification include sentiment classification and news categorization. In this paper, we present a soft computing techniqu...
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Xiao Wang, Xi Lin, Rong Wang, Kai-Qi Fan, Li-Jun Han and Zhao-Yuan Ding
DNA N4-methylcytosine(4mC) plays an important role in numerous biological functions and is a mechanism of particular epigenetic importance. Therefore, accurate identification of the 4mC sites in DNA sequences is necessary to understand the functional mec...
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Yadong Yang, Xiaofeng Wang, Quan Zhao and Tingting Sui
The focus of fine-grained image classification tasks is to ignore interference information and grasp local features. This challenge is what the visual attention mechanism excels at. Firstly, we have constructed a two-level attention convolutional network...
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Qingyong Zhang, Changhuan Song and Yiqing Yuan
Vehicle gearboxes are subject to strong noise interference during operation, and the noise in the signal affects the accuracy of fault identification. Signal denoising and fault diagnosis processes are often conducted independently, overlooking their syn...
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Ying-Hsun Lai, Shin-Yeh Chen, Wen-Chi Chou, Hua-Yang Hsu and Han-Chieh Chao
Federated learning trains a neural network model using the client?s data to maintain the benefits of centralized model training while maintaining their privacy. However, if the client data are not independently and identically distributed (non-IID) becau...
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Shaona Wang, Yang Liu and Linlin Li
In this study, a novel feature learning method for synthetic aperture radar (SAR) image automatic target recognition is presented. It is based on spatial pyramid matching (SPM), which represents an image by concatenating the pooling feature vectors that ...
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