Motor Cortical Networks for Skilled Movements Have Dynamic Properties That Are Related to Accurate Reaching by David F. Putrino, Zhe Chen, Soumya Ghosh, Emery N. Brown

“…Neurons in the Primary Motor Cortex (MI) are known to form functional ensembles with one another in order to produce voluntary movement. Neural network changes during skill learning are thought to be involved in improved fluency and accuracy of motor tasks. …”
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An End-to-End Rumor Detection Model Based on Feature Aggregation by Aoshuang Ye, Lina Wang, Run Wang, Wenqi Wang, Jianpeng Ke, Danlei Wang

“…In this paper, a deep neural network- (DNN-) based feature aggregation modeling method is proposed, which makes full use of the knowledge of propagation pattern feature and text content feature of social network event without feature engineering and domain knowledge. …”
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Theory and Numerical Analysis of Extreme Learning Machine and Its Application for Different Degrees of Defect Recognition of Hoisting Wire Rope by Zhike Zhao, Xiaoguang Zhang

“…ELM was proposed based on the single-hidden layer feed-forward neural network (SLFNN). ELM is characterized by the easier parameter selection rules, the faster converge speed, the less human intervention, and so on. …”
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Estimating Body Related Soft Biometric Traits in Video Frames by Olasimbo Ayodeji Arigbabu, Sharifah Mumtazah Syed Ahmad, Wan Azizun Wan Adnan, Salman Yussof, Vahab Iranmanesh, Fahad Layth Malallah

“…This paper presents an approach for estimating body related soft biometrics; specifically we propose a new approach based on body measurement and artificial neural network for predicting body weight of subjects and incorporate the existing technique on single view metrology for height estimation in videos with low frame rate. …”
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An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning by S. M. Taslim Uddin Raju, Amlan Sarker, Apurba Das, Md. Milon Islam, Mabrook S. Al-Rakhami, Atif M. Al-Amri, Tasniah Mohiuddin, Fahad R. Albogamy

“…Different machine learning (ML) approaches, including support vector regression (SVR), extreme learning machine (ELM), and multilayer perceptron neural network (MLP), are adopted as reference models. …”
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Application of deconvolutional networks for feature interpretability in epilepsy detection by Sihao Shao, Yu Zhou, Ruiheng Wu, Aiping Yang, Qiang Li

“…The Fully Convolutional Network (FCN) can provide the model’s interpretability but has not been applied in seizure detection.MethodsTo address these challenges, a novel convolutional neural network (CNN) model, combining SE (Squeeze-and-Excitation) modules, was proposed on top of the FCN. …”
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COVID-19 Deep Learning Prediction Model Using Publicly Available Radiologist-Adjudicated Chest X-Ray Images as Training Data: Preliminary Findings by Mohd Zulfaezal Che Azemin, Radhiana Hassan, Mohd Izzuddin Mohd Tamrin, Mohd Adli Md Ali

“…We used a deep learning model based on the ResNet-101 convolutional neural network architecture, which was pretrained to recognize objects from a million of images and then retrained to detect abnormality in chest X-ray images. …”
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Improved feature reduction framework for sign language recognition using autoencoders and adaptive Grey Wolf Optimization by Rajeev Goel, Sandhya Bansal, Kavita Gupta

“…A handcrafted artificial neural network serves as the classifier within this integrated framework, denoted as AEGWO-Net. …”
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An Artificial Intelligence Mechanism for the Prediction of Signal Strength in Drones to IoT Devices in Smart Cities by Mohamad Reda A. Refaai, Vinjamuri S. N. C. H. Dattu, H. S. Niranjana Murthy, P. Pramod Kumar, B. Kannadasan, Abdi Diriba

“…Depending on many relevant criteria, an artificial neural network (ANN)-centered precise and effective method is provided to forecast the signal strength from such drones. …”
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Postcare for Repairing Nerve and Tendon Injury Based on Biomimetic Nano-Parallel Material Composite Protein by Junxia Fu, Xiaohong Tan, Yan Tang

“…It can use the BP algorithm in the neural network algorithm to simulate the parallel arrangement of tendon collagen fibers, which is more efficient than other schemes. …”
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A Novel Approach of Label Construction for Predicting Remaining Useful Life of Machinery by Hailong Lin, Zihao Lei, Guangrui Wen, Xiaojun Tian, Xin Huang, Jinsong Liu, Haoxuan Zhou, Xuefeng Chen

“…Finally, the recurrent neural network (RNN) is used for prediction and verification. …”
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A Hierarchical Attention Recommender System Based on Cross-Domain Social Networks by Rongmei Zhao, Xi Xiong, Xia Zu, Shenggen Ju, Zhongzhi Li, Binyong Li

“…Recently, the recommendation algorithm of graph neural network based on social network has greatly improved the quality of the recommendation system. …”
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ARM-Cortex M3-Based Two-Wheel Robot for Assessing Grid Cell Model of Medial Entorhinal Cortex: Progress towards Building Robots with Biologically Inspired Navigation-Cognitive Maps by J. Cuneo, L. Barboni, N. Blanco, M. del Castillo, J. Quagliotti

“…It is considered that the results of this work provide an insight into achieving an enhanced embedded systems design for emulating and understanding mathematical neural network models to be used as biologically inspired navigation system for robots.…”
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Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images by Avigyan Roy, Priyam Saha, Nandita Gautam, Friedhelm Schwenker, Ram Sarkar

“…They are an essential tool in the study and understanding of diseases, aiding in research, education, and patient care. Convolutional neural network based pretrained deep learning models can be used successfully to detect lung cancer. …”
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Func-Bagging: An Ensemble Learning Strategy for Improving the Performance of Heterogeneous Anomaly Detection Models by Ruinan Qiu, Yongfeng Yin, Qingran Su, Tianyi Guan

“…Additionally, we design a specialized neural network, and by training it adequately, validate the rationality of the proposed adaptive weight distribution strategy, further improving the model’s robustness. …”
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CoLR: Classification-Oriented Local Representation for Image Recognition by Tan Guo, Lei Zhang, Xiaoheng Tan, Liu Yang, Zhiwei Guo, Fupeng Wei

“…Specifically, the deep features of the object dataset are obtained by a well-trained convolutional neural network (CNN) with five convolutional layers and three fully connected layers on the challenging ImageNet. …”
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A Channel Attention-Driven Optimized CNN for Efficient Early Detection of Plant Diseases in Resource Constrained Environment by Sana Parez, Naqqash Dilshad, Jong Weon Lee

“…To address this, we propose a lightweight convolutional neural network (CNN) designed for resource-constrained devices termed as <i>LeafNet</i>. …”
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EfficientNet-b0-Based 3D Quantification Algorithm for Rectangular Defects in Pipelines by Di Wu, Yong Hong, Jie Wang, Shaojun Wu, Zhihao Zhang, Yizhang Liu

“…This research introduces EffiTriDimNet (ETDN), a multi-task convolutional neural network that combines one-dimensional pipeline defect leakage detection data into a unified feature map while simultaneously measuring the three-dimensional characteristics of the defects. …”
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Multimodal Data Fusion for Depression Detection Approach by Mariia Nykoniuk, Oleh Basystiuk, Nataliya Shakhovska, Nataliia Melnykova

“…These networks were developed using convolutional neural network (CNN) layers to learn local patterns, a bidirectional LSTM (Bi-LSTM) to process sequences, and a self-attention mechanism to improve focus on key parts of the data. …”
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A Prediction Model of Structural Settlement Based on EMD-SVR-WNN by Xianglong Luo, Wenjuan Gan, Lixin Wang, Yonghong Chen, Xue Meng

“…Aiming at the problems in the structural deformation prediction model and considering the internal characteristics of deformation monitoring data and the influence of different components in the data on the prediction accuracy, a combined prediction model based on the Empirical Mode Decomposition, Support Vector Regression, and Wavelet Neural Network (EMD-SVR-WNN) is proposed. EMD model is used to decompose the structure settlement monitoring data, and the settlement data can be effectively divided into relatively stable trend terms and residual components of random fluctuation by energy matrix. …”
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