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Gulsum Alicioglu and Bo Sun
Deep learning (DL) models have achieved state-of-the-art performance in many domains. The interpretation of their working mechanisms and decision-making process is essential because of their complex structure and black-box nature, especially for sensitiv...
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Lina Zhou, Leijinyu Zhou, Hongbo Wu, Tingting Jing, Tianhao Li, Jinsheng Li, Lijuan Kong and Limei Chen
In order to monitor cadmium contamination in lettuce quickly, non-invasively, and accurately, and to understand the growth status of lettuce under cadmium pollution, lettuce was used as the test material to detect and analyze the visible?near-infrared re...
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Benjamin Jahic, Nicolas Guelfi and Benoît Ries
Neural network (NN) components are being increasingly incorporated into software systems. Neural network properties are determined by their architecture, as well as the training and testing datasets used. The engineering of datasets and neural networks i...
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M. Guru Vimal Kumar, Veena N, Lenka Cepová, M Arun Manicka Raja, Allam Balaram and Muniyandy Elangovan
Agriculture is the backbone of any developing or developed country that makes any living to survive. To make food available throughout the year, it is necessary to know about agriculture and the work and strategies involved. Hence, agricultural courses h...
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Ganapathy Ramesh, Jaganathan Logeshwaran, Thangavel Kiruthiga and Jaime Lloret
In general, reliable PV generation prediction is required to increase complete control quality and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV power production could limit the influence of uncertainties on photovol...
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Dhan Lord B. Fortela, Armani Travis, Ashley P. Mikolajczyk, Wayne Sharp, Emmanuel Revellame, William Holmes, Rafael Hernandez and Mark E. Zappi
Wastewater (WW) analysis is a critical step in various operations, such as the control of a WW treatment facility, and speeding up the analysis of WW quality can significantly improve such operations. This work demonstrates the capability of neural netwo...
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Saeid Khaksari Nezhad, Mohammad Barooni, Deniz Velioglu Sogut and Robert J. Weaver
This review paper focuses on the use of ensemble neural networks (ENN) in the development of storm surge flood models. Storm surges are a major concern in coastal regions, and accurate flood modeling is essential for effective disaster management. Neural...
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Irina Nizovtseva, Vladimir Palmin, Ivan Simkin, Ilya Starodumov, Pavel Mikushin, Alexander Nozik, Timur Hamitov, Sergey Ivanov, Sergey Vikharev, Alexei Zinovev, Vladislav Svitich, Matvey Mogilev, Margarita Nikishina, Simon Kraev, Stanislav Yurchenko, Timofey Mityashin, Dmitrii Chernushkin, Anna Kalyuzhnaya and Felix Blyakhman
Development of energy-efficient and high-performance bioreactors requires progress in methods for assessing the key parameters of the biosynthesis process. With a wide variety of approaches and methods for determining the phase contact area in gas?liquid...
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Zahra Jafari and Ebrahim Karami
The prompt and accurate diagnosis of breast lesions, including the distinction between cancer, non-cancer, and suspicious cancer, plays a crucial role in the prognosis of breast cancer. In this paper, we introduce a novel method based on feature extracti...
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Ana Ramos Oliveira, Tiago Brito Ramos and Ramiro Neves
This study compares the performance of three different neural network models to estimate daily streamflow in a watershed under a natural flow regime. Based on existing and public tools, different types of NN models were developed, namely, multi-layer per...
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