Finite-Time Projective Synchronization of Fractional-Order Memristive Neural Networks with Mixed Time-Varying Delays by Meng Hui, Chen Wei, Jiao Zhang, Herbert Ho-Ching Iu, Ni Luo, Rui Yao, Lin Bai

“…This paper is concerned with the finite-time projective synchronization problem of fractional-order memristive neural networks (FMNNs) with mixed time-varying delays. …”
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Comparison of intensity normalization methods in prostate, brain, and breast cancer multi-parametric magnetic resonance imaging by Savannah R. Duenweg, Samuel A. Bobholz, Allison K. Lowman, Aleksandra Winiarz, Biprojit Nath, Michael J. Barrett, Fitzgerald Kyereme, Stephanie Vincent-Sheldon, Peter LaViolette

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Delay-Dependent Guaranteed Cost Controller Design for Uncertain Neural Networks with Interval Time-Varying Delay by M. Rajchakit, P. Niamsup, T. Rojsiraphisal, G. Rajchakit

“…This paper studies the problem of guaranteed cost control for a class of uncertain delayed neural networks. The time delay is a continuous function belonging to a given interval but not necessary to be differentiable. …”
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Strength Investigation of the Silt-Based Cemented Paste Backfill Using Lab Experiments and Deep Neural Network by Chongchun Xiao, Xinmin Wang, Qiusong Chen, Feng Bin, Yihan Wang, Wei Wei

“…After the discussion of the experimental results, a dataset was prepared after data collection and processing. Deep neural network (DNN) was employed to predict the UCS of CPB from its influencing variables, namely, the proportion of OPC, CG, CFA, and YS, the solids content, and the curing time. …”
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3D Automatic Segmentation of Brain Tumor Based on Deep Neural Network and Multimodal MRI Images by Zhuliang Qian, Lifeng Xie, Yisheng Xu

“…In addition, this paper constructs an automatic diagnosis system for brain tumors, uses GLCM and discrete wavelet transform (DWT) to extract features from MRI images, and then uses a convolutional neural network (CNN) for final diagnosis; finally, through four. …”
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New Results for Periodic Solution of High-Order BAM Neural Networks with Continuously Distributed Delays and Impulses by Chang-Bo Yang, Ting-Zhu Huang, Jin-Liang Shao

“…By M-matrix theory, inequality techniques, and Lyapunov functional method, certain sufficient conditions are obtained to ensure the existence, uniqueness, and global exponential stability of periodic solution for a new type of high-order BAM neural networks with continuously distributed delays and impulses. …”
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Adsorption Behaviour of Normal Paraffins in a Fixed Bed Adsorber Containing 5 Å Molecular Sieves by Liu Jichang, Shen Benxian, Sun Hui

“…Long-chain normal paraffins had a notable displacement desorption relative to short-chain normal paraffins.…”
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The Impact of Pixel Resolution, Integration Scale, Preprocessing, and Feature Normalization on Texture Analysis for Mass Classification in Mammograms by Mohamed Abdel-Nasser, Jaime Melendez, Antonio Moreno, Domenec Puig

“…In this paper, we study the effect of factors such as pixel resolution, integration scale, preprocessing, and feature normalization on the performance of those texture methods for mass classification. …”
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Physics-Informed Neural Network-Based Input Shaping for Vibration Suppression of Flexible Single-Link Robots by Tingfeng Li, Tengfei Xiao

Subjects: “…physics-informed neural network (PINN)…”
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A novel hybrid inception-xception convolutional neural network for efficient plant disease classification and detection by Wasswa Shafik, Ali Tufail, Chandratilak Liyanage De Silva, Rosyzie Anna Awg Haji Mohd Apong

“…This study presents a novel hybrid inception-xception (IX) using a convolution neural network (CNN). The presented model combines inception and depth-separable convolution layers to capture multiple-scale features while reducing model complexity and overfitting. …”
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Event-Triggered State Estimation for a Class of Delayed Recurrent Neural Networks with Sampled-Data Information by Hongjie Li

“…The paper investigates the state estimation problem for a class of recurrent neural networks with sampled-data information and time-varying delays. …”
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Adaptive Event-Triggered Synchronization of Networked Neural Networks with Time-Varying Delay Subject to Actuator Saturation by Yao Xu, Renren Wang, Hongqian Lu, Xingxing Song, Yahan Deng, Wuneng Zhou

“…This paper discusses the adaptive event-triggered synchronization problem of a class of neural networks (NNs) with time-varying delay and actuator saturation. …”
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Adaptive Neural Network Variable Structure Control for Liquid-Filled Spacecraft under Unknown Input Saturation by Hongwei Wang, Shufeng Lu, Xiaojuan Song

“…This study addresses the problem of attitude maneuver control for a three-axis stabilized liquid-filled spacecraft using an adaptive neural network variable structure control algorithm in the presence of parametric uncertainty, external disturbances, and control input saturation. …”
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3D Face Modeling Algorithm for Film and Television Animation Based on Lightweight Convolutional Neural Network by Cheng Di, Jing Peng, Yihua Di, Siwei Wu

“…Through the analysis of facial feature extraction technology, this paper designs a lightweight convolutional neural network (LW-CNN). The LW-CNN model adopts a separable convolution structure, which can propose more accurate features with fewer parameters and can extract 3D feature points of a human face. …”
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A mechanism-informed deep neural network enables prioritization of regulators that drive cell state transitions by Xi Xi, Jiaqi Li, Jinmeng Jia, Qiuchen Meng, Chen Li, Xiaowo Wang, Lei Wei, Xuegong Zhang

“…This method to analyze single-cell multi-omics data demonstrates how the interpretable design of neural networks can better decode biological systems.…”
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A Hybrid Approach for Modular Neural Network Design Using Intercriteria Analysis and Intuitionistic Fuzzy Logic by Sotir Sotirov, Evdokia Sotirova, Vassia Atanassova, Krassimir Atanassov, Oscar Castillo, Patricia Melin, Todor Petkov, Stanimir Surchev

“…Here, the proposed method is applied to study the behavior of one type of neural networks, the modular neural networks (MNN), that combine several simple neural models for simplifying a solution to a complex problem. …”
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Identification of Molecular Signatures in Neural Differentiation and Neurological Diseases Using Digital Color-Coded Molecular Barcoding by Debora Salerno, Alessandro Rosa

“…In order to fully exploit the potential of PSCs, advanced methods that facilitate the identification of molecular signatures in neural differentiation and neurological diseases are highly demanded. …”
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An Efficient 3D Convolutional Neural Network for Dose Prediction in Cancer Radiotherapy from CT Images by Lam Thanh Hien, Pham Trung Hieu, Do Nang Toan

“…<b>Materials and Methods</b>: In this paper, we propose a custom 3D convolutional neural network model with a U-Net-based architecture to automatically predict radiation doses during cancer radiation therapy from CT images. …”
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C1-Almost Periodic Solutions of BAM Neural Networks with Time-Varying Delays on Time Scales by Yongkun Li, Lili Zhao, Li Yang

“…On a new type of almost periodic time scales, a class of BAM neural networks is considered. By employing a fixed point theorem and differential inequality techniques, some sufficient conditions ensuring the existence and global exponential stability of C1-almost periodic solutions for this class of networks with time-varying delays are established. …”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

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