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Mahsa Yousefi and Ángeles Martínez
While first-order methods are popular for solving optimization problems arising in deep learning, they come with some acute deficiencies. To overcome these shortcomings, there has been recent interest in introducing second-order information through quasi...
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Aristeidis Karras, Christos Karras, Nikolaos Schizas, Markos Avlonitis and Spyros Sioutas
The field of automated machine learning (AutoML) has gained significant attention in recent years due to its ability to automate the process of building and optimizing machine learning models. However, the increasing amount of big data being generated ha...
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Joseph Isabona, Agbotiname Lucky Imoize, Oluwasayo Akinloye Akinwumi, Okiemute Roberts Omasheye, Emughedi Oghu, Cheng-Chi Lee and Chun-Ta Li
Benchmarking different optimization algorithms is tasky, particularly for network-based cellular communication systems. The design and management process of these systems involves many stochastic variables and complex design parameters that demand an unb...
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Xiangpeng Fan and Zhibin Guan
The automatic recognition of crop diseases based on visual perception algorithms is one of the important research directions in the current prevention and control of crop diseases. However, there are two issues to be addressed in corn disease identificat...
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Pablo Moscato, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan and Jonathon Corrales de Oliveira
In the field of Artificial Intelligence (AI) and Machine Learning (ML), a common objective is the approximation of unknown target functions y=f(x)" role="presentation">??=??(??)y=f(x)
y
=
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using limited instances S=(x(i),y(i))" role="presentation...
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Xuanzhi Liao, Shahnorbanun Sahran, Azizi Abdullah and Syaimak Abdul Shukor
Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their prob...
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Tahani Alqurashi
Arabic dialect identification (ADI) has recently drawn considerable interest among researchers in language recognition and natural language processing fields. This study investigated the use of a character-level model that is effectively unrestricted in ...
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Angona Biswas,Md. Saiful Islam
Pág. 42 - 55
Background: Handwriting recognition becomes an appreciable research area because of its important practical applications, but varieties of writing patterns make automatic classification a challenging task. Classifying handwritten digits with a higher acc...
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Dokkyun Yi, Jaehyun Ahn and Sangmin Ji
A machine is taught by finding the minimum value of the cost function which is induced by learning data. Unfortunately, as the amount of learning increases, the non-liner activation function in the artificial neural network (ANN), the complexity of the a...
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Lin Zhang, Yian Zhu, Xianchen Shi and Xuesi Li
To improve the intelligence and accuracy of the Situation Assessment (SA) in complex scenes, this work develops an improved fuzzy deep neural network approach to the situation assessment for multiple Unmanned Aerial Vehicle(UAV)s. Firstly, this work norm...
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