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Musab T. S. Al-Kaltakchi, Ahmad Saeed Mohammad and Wai Lok Woo
Speech separation is a well-known problem, especially when there is only one sound mixture available. Estimating the Ideal Binary Mask (IBM) is one solution to this problem. Recent research has focused on the supervised classification approach. The chall...
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Broderick Crawford, Felipe Cisternas-Caneo, Katherine Sepúlveda, Ricardo Soto, Álex Paz, Alvaro Peña, Claudio León de la Barra, Eduardo Rodriguez-Tello, Gino Astorga, Carlos Castro, Franklin Johnson and Giovanni Giachetti
The digitization of information and technological advancements have enabled us to gather vast amounts of data from various domains, including but not limited to medicine, commerce, and mining. Machine learning techniques use this information to improve d...
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Suping Wang, Ligu Zhu, Lei Shi, Hao Mo and Songfu Tan
Cross-modal retrieval aims to elucidate information fusion, imitate human learning, and advance the field. Although previous reviews have primarily focused on binary and real-value coding methods, there is a scarcity of techniques grounded in deep repres...
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Sapna Sadhwani, Baranidharan Manibalan, Raja Muthalagu and Pranav Pawar
The study in this paper characterizes lightweight IoT networks as being established by devices with few computer resources, such as reduced battery life, processing power, memory, and, more critically, minimal security and protection, which are easily vu...
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Jesús Dassaef López-Barrios, Jesús Arturo Escobedo Cabello, Alfonso Gómez-Espinosa and Luis-Enrique Montoya-Cavero
In this paper, a mask region-based convolutional neural network (Mask R-CNN) is used to improve the performance of machine vision in the challenging task of detecting peduncles and fruits of green sweet peppers (Capsicum annuum L.) in greenhouses. One of...
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