Retracted: Classification of Myopathy and Amyotrophic Lateral Sclerosis Electromyograms Using Bat Algorithm and Deep Neural Networks by Behavioural Neurology

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A Customized Deep Neural Network Approach to Investigate Travel Mode Choice with Interpretable Utility Information by Zhengchao Zhang, Congyuan Ji, Yineng Wang, Yanni Yang

“…Thus far, this field has been dominated by multinomial logit (MNL) models with a linear utility specification. However, deep neural networks (DNNs), owing to their powerful capacity of nonlinear fitting, are now rapidly replacing these models. …”
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Hybridizing Evolutionary Computation and Deep Neural Networks: An Approach to Handwriting Recognition Using Committees and Transfer Learning by Alejandro Baldominos, Yago Saez, Pedro Isasi

“…In this paper, we rely on previous work to apply neuroevolution in order to optimize the topology of deep neural networks that can be used to solve the problem of handwritten character recognition. …”
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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

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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

“…Here, we present regX, a deep neural network incorporating both gene-level regulation and gene-gene interaction mechanisms, which enables prioritizing potential driver regulators of cell state transitions and providing mechanistic interpretations. …”
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Cyclic Training of Dual Deep Neural Networks for Discovering User and Item Latent Traits in Recommendation Systems by Dohyoung Rim, Sirojiddin Nuriev, Younggi Hong

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GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force by Chandrasen Pandey, Diptendu Sinha Roy, Ramesh Chandra Poonia, Ayman Altameem, Soumya Ranjan Nayak, Amit Verma, Abdul Khader Jilani Saudagar

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Battery State of Charge and State of Health Estimation Using a New Hybrid Deep Neural Network Approach by Saeid Jorkesh, Ryan Ahmed, Saeid Habibi, Reza Hosseininejad, Siyuan Xu

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Monte Carlo Noise Reduction Algorithm Based on Deep Neural Network in Efficient Indoor Scene Rendering System by Xiwen Chen, Jianfei Shen

“…For this problem, we propose a Monte Carlo noise reduction algorithm based on deep neural networks and apply it to the efficient rendering of an indoor scene. …”
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A Review on Inverse Kinematics, Control and Planning for Robotic Manipulators With and Without Obstacles via Deep Neural Networks by Ana Calzada-Garcia, Juan G. Victores, Francisco J. Naranjo-Campos, Carlos Balaguer

“…This article presents a literature review of the advances made in the past five years in the use of Deep Neural Networks (DNN) for IK with regard to control and planning with and without obstacles for rigid robotic manipulators. …”
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Evaluation Method of Music Teaching Effect Based on Fusion of Deep Neural Network under the Background of Big Data by Yifan Fan

“…Because there is a strong subjectivity in the evaluation of the teaching effect of music subjects, this study combines deep neural network technology to study the feasibility and accuracy of the convolutional neural network (CNN) and long short-term memory neural network (LSTM) method in the evaluation of music teaching effects. …”
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Adaptive temporal-difference learning via deep neural network function approximation: a non-asymptotic analysis by Guoyong Wang, Tiange Fu, Ruijuan Zheng, Xuhui Zhao, Junlong Zhu, Mingchuan Zhang

“…In order to mitigate this issue, we propose an adaptive neural TD algorithm (AdaBNTD) inspired by the superior performance of adaptive gradient techniques in training deep neural networks. Simultaneously, we derive non-asymptotic bounds for AdaBNTD within the Markovian observation framework. …”
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Optimal adjustment of deep neural network parameters in estimating lost vital sign data in body wireless sensor networks by Aboulfazl Ebrahimi, Mahboubeh Shamsi, Morteza Mohajjel

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AI-driven prediction of drug activity against Toxoplasma gondii: Data augmentation and deep neural networks for limited datasets by Natalia V. Karimova, Ravithree D. Senanayake

“…This Artificial Intelligence (AI)-driven Quantitative Structure-Activity Relationship (QSAR) study applies deep neural networks (DNNs) to predict pIC50 values for potential inhibitors, using 2D and 3D molecular descriptors and fingerprints. …”
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Analysis of Protein-Ligand Interactions of SARS-CoV-2 Against Selective Drug Using Deep Neural Networks by Natarajan Yuvaraj, Kannan Srihari, Selvaraj Chandragandhi, Rajan Arshath Raja, Gaurav Dhiman, Amandeep Kaur

Subjects: “…deep neural network (dnn)…”
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Mapping fruit tree dynamics using phenological metrics from optimal Sentinel-2 data and Deep Neural Network by Yingisani Chabalala, Elhadi Adam, Mahlatse Kganyago

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Optimal Multi-Physics Synthesis of a Dual-Frequency Power Inductor Using Deep Neural Networks and Gaussian Process Regression by Paolo Di Barba, Arash Ghafoorinejad, Maria Evelina Mognaschi, Fabrizio Dughiero, Michele Forzan, Elisabetta Sieni

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MRM-BERT: a novel deep neural network predictor of multiple RNA modifications by fusing BERT representation and sequence features by Linshu Wang, Yuan Zhou

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Paying attention to the SARS-CoV-2 dialect : a deep neural network approach to predicting novel protein mutations by Magdalyn E. Elkin, Xingquan Zhu

“…In this paper, we propose a Deep Novel Mutation Search (DNMS) method, using deep neural networks, to model protein sequence for mutation prediction. …”
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