Comparative Analysis of CNN-Based Semantic Segmentation for Apple Tree Canopy Size Recognition in Automated Variable-Rate Spraying by Tantan Jin, Su Min Kang, Na Rin Kim, Hye Ryeong Kim, Xiongzhe Han

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CNN-Based Optimization for Fish Species Classification: Tackling Environmental Variability, Class Imbalance, and Real-Time Constraints by Amirhosein Mohammadisabet, Raza Hasan, Vishal Dattana, Salman Mahmood, Saqib Hussain

“…However, challenges such as environmental variability, class imbalance, and computational demands hinder the development of robust classification models. …”
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Development of a novel deep learning method that transforms tabular input variables into images for the prediction of SLD by Gabriel Cubillos, Javier Perez-Valenzuela, Herman Aguirre, Luz Martínez, Lorena Castro, Gabriel Mezzano, Claudio A. Perez

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Singular distributions of random variables with independent digits of representation in numeral system with natural base and redundant alphabet by M. V. Pratsiovytyi, S. P. Ratushniak

“…Given natural parameters $s$ and $r$, where $2\leq s\leq r$, we consider the distribution of a~ran\-dom variable $$\xi=\sum\limits_{k=1}^{\infty}s^{-k}\xi_k\equiv\Delta^{r_s}_{\xi_1\xi_2...…”
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Multi-Scale Building Load Forecasting Without Relying on Weather Forecast Data: A Temporal Convolutional Network, Long Short-Term Memory Network, and Self-Attention Mechanism Appro... by Lanqian Yang, Jinmin Guo, Huili Tian, Min Liu, Chang Huang, Yang Cai

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Estimates for convolutions in the anisotropic Nikol'skiĭ-Besov spaces by V. I. Burenkov, G. E. García Almeida

“…We obtain various estimates for convolutions in the anisotropic Nikol'skiĭ-Besov spaces of functions of several real variables possessing some common smoothness of, in general, fractional order which may be different with respect to different variables.…”
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On the Convolution Equation Related to the Diamond Klein-Gordon Operator by Amphon Liangprom, Kamsing Nonlaopon

“…We study the distribution eαx(♢+m2)kδ for m≥0, where (♢+m2)k is the diamond Klein-Gordon operator iterated k times, δ is the Dirac delta distribution, x=(x1,x2,…,xn) is a variable in ℝn, and α=(α1,α2,…,αn) is a constant. In particular, we study the application of eαx(♢+m2)kδ for solving the solution of some convolution equation. …”
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Convolutional neural networks for accurate estimation of canopy cover by F. Puig, R. Gonzalez Perea, A. Daccache, M.A. Soriano, J.A. Rodríguez Díaz

“…Canopy Cover (CC) is a key variable in agriculture, providing critical information on crop growth and health. …”
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Unraveling Parkinson's disease motor subtypes: A deep learning approach based on spatiotemporal dynamics of EEG microstates by Lin Meng, Deyu Wang, Jun Ma, Yu Shi, Hongbo Zhao, Yanlin Wang, Qingqing Shi, Xiaodong Zhu, Dong Ming

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Predicting species distributions in the open ocean with convolutional neural networks by Morand, Gaétan, Joly, Alexis, Rouyer, Tristan, Lorieul, Titouan, Barde, Julien

“…Indeed, tracking species distributions in the open ocean is particularly challenging due to the scarcity of observations and the complex and variable nature of the ocean system. In this study, we propose a new method that leverages deep learning, specifically convolutional neural networks (CNNs), to capture spatial features of environmental variables. …”
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Hybrid Clayton-Frank Convolution-Based Bivariate Archimedean Copula by Maxwell Akwasi Boateng, Akoto Yaw Omari-Sasu, Richard Kodzo Avuglah, Nana Kena Frempong

“…This study exploits the closure property of the converse convolution operator to come up with a hybrid Clayton-Frank Archimedean copula for two random variables. …”
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The Laguerre transform of a convolution product of vector-valued functions. by A. O. Muzychuk

“…The Laguerre transform is applied to the convolution product of functions of a real argument (over the time axis) with values in Hilbert spaces. …”
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Some properties of convolution and spherical analysis on the Euclidean motion group by Uwe Edeke, Unanaowo Bassey

“…It is demonstrated that this convolution is homogeneous, smooth and satisfies the moment condition. …”
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Complementing Dynamical Downscaling With Super‐Resolution Convolutional Neural Networks by Deeksha Rastogi, Haoran Niu, Linsey Passarella, Salil Mahajan, Shih‐Chieh Kao, Pouya Vahmani, Andrew D. Jones

“…Future work will expand this methodology to downscale additional variables for future climate projections.…”
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Detection and Classification of Sporadic E Using Convolutional Neural Networks by J. A. Ellis, D. J. Emmons, M. B. Cohen

“…Abstract In this work, convolutional neural networks (CNN) are developed to detect and characterize sporadic E (Es), demonstrating an improvement over current methods. …”
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English Text Recognition Based on Convolutional Neural Network (CNN) by Razia Maroof, Irfan Ahmed Usmani, Atruba Feroze

“…Traditional methods attain an imperfect ability to handle such variability and complexity. This study addresses the text recognition problem from images, directing the extraction of text from images with higher accuracy. …”
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Ocean wave power forecasting using convolutional neural networks by Pedro Bento, José Pombo, Maria do Rosário Calado, Sílvio Mariano

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Fault Diagnosis for Imbalanced Datasets Based on Deep Convolution Fuzzy System by Junwei Zhu, Linfang Zhu

“…The BAVAE improves data generation capabilities by introducing autoregressive distributions to learn latent variables, iteratively obtaining complex high-order latent variables, and amplifying inter-class differences through the introduction of feature discrimination loss during training. …”
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Detecting small seamounts in multibeam data using convolutional neural networks by Tobias Ziolkowski, Colin W. Devey, Agnes Koschmider

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Crop classification with deep convolutional neural network based on crop feature by Mohamad Reza Gili, Davoud Ashourloo, Hosein Aghighi, Ali Akbar Matkan, Alireza SHakiba

“…Agricultural land cover is relatively dynamic and variable at relatively short intervals. This makes it difficult to classify crops on satellite imagery (Bargiel, 2017). …”
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