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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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Christian Moya and Guang Lin
The Deep Operator Network (DeepONet) framework is a different class of neural network architecture that one trains to learn nonlinear operators, i.e., mappings between infinite-dimensional spaces. Traditionally, DeepONets are trained using a centralized ...
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Jialu Sui and Jian Yin
Nowadays, as the number of items is increasing and the number of items that users have access to is limited, user-item preference matrices in recommendation systems are always sparse. This leads to a data sparsity problem. The latent factor analysis (LFA...
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Jaka Tirta Samudra,B. Herawan Hayadi
Pág. 435 - 441
Dengan pesatnya pertumbuhan koperasi di Indonesia, maka pemberian kredit bagi anggota koperasi semakin diperketat dengan melakukan survey terhadap calon penerima kredit melalui analisis 5C yaitu character, capacity, capital, condition of economic dan eco...
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Jaka Tirta Samudra,B. Herawan Hayadi
Pág. 435 - 441
Dengan pesatnya pertumbuhan koperasi di Indonesia, maka pemberian kredit bagi anggota koperasi semakin diperketat dengan melakukan survey terhadap calon penerima kredit melalui analisis 5C yaitu character, capacity, capital, condition of economic dan eco...
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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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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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Dennis Delali Kwesi Wayo, Sonny Irawan, Alfrendo Satyanaga and Jong Kim
Data-driven models with some evolutionary optimization algorithms, such as particle swarm optimization (PSO) and ant colony optimization (ACO) for hydraulic fracturing of shale reservoirs, have in recent times been validated as one of the best-performing...
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Nikola ?igulic, Matko Glucina, Ivan Lorencin and Dario Matika
This study delves into the vital missions of the armed forces, encompassing the defense of territorial integrity, sovereignty, and support for civil institutions. Commanders grapple with crucial decisions, where accountability underscores the imperative ...
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Gregorius Ryan, Pricillia Katarina and Derwin Suhartono
The rise of social media as a platform for self-expression and self-understanding has led to increased interest in using the Myers?Briggs Type Indicator (MBTI) to explore human personalities. Despite this, there needs to be more research on how other wor...
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Cong Xie, Oluwasanmi Koyejo and Indranil Gupta
Distributed machine learning is primarily motivated by the promise of increased computation power for accelerating training and mitigating privacy concerns. Unlike machine learning on a single device, distributed machine learning requires collaboration a...
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Arthur Fournier, Franjieh El Khoury and Samuel Pierre
The rapid adoption of Android devices comes with the growing prevalence of mobile malware, which leads to serious threats to mobile phone security and attacks private information on mobile devices. In this paper, we designed and implemented a model for m...
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Manuel Domínguez-Rodrigo, Ander Fernández-Jaúregui, Gabriel Cifuentes-Alcobendas and Enrique Baquedano
Deep learning models are based on a combination of neural network architectures, optimization parameters and activation functions. All of them provide exponential combinations whose computational fitness is difficult to pinpoint. The intricate resemblanc...
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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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Matteo Grimaldi, Valerio Tenace and Andrea Calimera
Convolutional Neural Networks (CNNs) are brain-inspired computational models designed to recognize patterns. Recent advances demonstrate that CNNs are able to achieve, and often exceed, human capabilities in many application domains. Made of several mill...
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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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Omar I. Dallal Bashi, Shymaa Mohammed Jameel, Yasir Mahmood Al Kubaisi, Husamuldeen K. Hameed and Ahmad H. Sabry
Security identification solutions against WLAN network attacks according to straightforward digital detectors, such as SSID, IP addresses, and MAC addresses, are not efficient in identifying such hacking or router impersonation. These detectors can be si...
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Shilpa Gite, Shruti Patil, Deepak Dharrao, Madhuri Yadav, Sneha Basak, Arundarasi Rajendran and Ketan Kotecha
Feature selection and feature extraction have always been of utmost importance owing to their capability to remove redundant and irrelevant features, reduce the vector space size, control the computational time, and improve performance for more accurate ...
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Kyeong Ryong Kim, Aaron Lim and Jae Hyung Cho
The exterior location of a user can be accurately determined using a global positioning system (GPS). However, accurately locating objects indoors poses challenges due to signal penetration limitations within buildings. In this study, an MLP with stochas...
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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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