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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Sudden Intrabulbar Amyloid Increase Simultaneously Disrupts Olfactory Bulb Oscillations and Odor Detection by Rebeca Hernández-Soto, Keila Dara Rojas-García, Fernando Peña-Ortega

“…Moreover, this loss of smell appears to be related to alterations in neural network activity in several olfactory-related circuits, including the OB, as has been observed in anesthetized animals and brain slices. …”
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Automatic Tracking and Characterization of Cumulonimbus Clouds from FY-2C Geostationary Meteorological Satellite Images by Yu Liu, Du-Gang Xi, Zhao-Liang Li, Chun-Xiang Shi

“…First, a seeded region growing (SRG) algorithm is used with artificial neural network (ANN) cloud classification as preprocessing to identify consistent homogeneous Cb patches from infrared images. …”
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Confirmation of Thermal Images and Vibration Signals for Intelligent Machine Fault Diagnostics by Achmad Widodo, Djoeli Satrijo, Toni Prahasto, Gang-Min Lim, Byeong-Keun Choi

“…This paper deals with the maintenance technique for industrial machinery using the artificial neural network so-called self-organizing map (SOM). The aim of this work is to develop intelligent maintenance system for machinery based on an alternative way, namely, thermal images instead of vibration signals. …”
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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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Acoustic Trauma Changes the Parvalbumin-Positive Neurons in Rat Auditory Cortex by Congli Liu, Tao Xu, Xiaopeng Liu, Yina Huang, Haitao Wang, Bin Luo, Jingwu Sun

“…Parvalbumin-containing neurons (PV neurons), a subset of GABAergic neurons, greatly shape and synchronize neural network activities. However, the change of PV neurons following acoustic trauma remains to be elucidated. …”
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Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine by Hang-cheong Wong, Pak-kin Wong, Chi-man Vong

“…This study shows that the accuracy, training, and updating time of the RVM model are superior to the latest modelling methods, such as diagonal recurrent neural network (DRNN) and decremental least-squares support vector machine (DLSSVM). …”
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A New Evaluation Method of Total Organic Carbon for Shale Source Rock Based on the Effective Medium Conductivity Theory by Jian Fu, Xuesong Li, Yonghe Sun, Qiuli Huo, Ting Gao, Li Fu, Yuchen Liu, Suxing Dong, Haijun Fan

“…At present, the commonly used methods for assessing TOC include △logR and neural network method. However, practice shows that these methods have limitations in the application of unconventional intervals of sand-shale interbeds, and they cannot sufficiently reflect the variation of TOC in the vertical direction. …”
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Applying in machine learning and deep learning in finance industry: A case study on repayment prediction by Nguyễn Phát Đạt, Hồ Mai Minh Nhật, Trương Công Vinh, Lê Quang Chấn Phong, Lê Hoành Sử

“…Employed techniques encompass Logistic Regression (LR), K-Nearest Neighbor (KNN), Extreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGBM), in conjunction with deep learning architectures such as Long Short-Term Memory (LSTM) and Artificial Neural Network (ANN). Following methodological refinement, it becomes apparent that ensemble learning approaches, exemplified by XGB and LGBM, exhibit markedly superior predictive performance, surpassing conventional models with an accuracy rate exceeding 85%. …”
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Coincidence Detection Using Spiking Neurons with Application to Face Recognition by Fadhlan Kamaruzaman, Amir Akramin Shafie, Yasir M. Mustafah

“…We elucidate the practical implementation of Spiking Neural Network (SNN) as local ensembles of classifiers. …”
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Deep Multiscale Soft-Threshold Support Vector Data Description for Enhanced Heavy-Duty Gas Turbine Generator Sets’ Anomaly Detection by Zhang Kun, Li Hongren, Wang Xin, Xie Daxing, Sun Xiaokai

“…The model combines a support vector data description (SVDD) with a deep autoencoder backbone network framework, integrating a multiscale convolutional neural network (M) and soft-threshold activation network (S) into the Deep-SVDD framework. …”
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Emotional recognition of EEG signals utilizing residual structure fusion in bi-directional LSTM by Yue Xu, Yunyuan Gao, Zhengnan Zhang, Shunlan Du

“…The experimental results demonstrated that the novel neural network model proposed in this paper had outperformed currently available methods in emotion recognition tasks.…”
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Rancidity Estimation of Perilla Seed Oil by Using Near-Infrared Spectroscopy and Multivariate Analysis Techniques by Suk-Ju Hong, Shin-Joung Rho, Ah-Yeong Lee, Heesoo Park, Jinshi Cui, Jongmin Park, Soon-Jung Hong, Yong-Ro Kim, Ghiseok Kim

“…Preprocessing methods were applied to the transmittance spectra of perilla seed oil, and multivariate analysis techniques, such as principal component regression (PCR), partial least squares regression (PLSR), and artificial neural network (ANN) modeling, were employed to develop the models. …”
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Weakly-Supervised Deep Shape-From-Template by Sara Luengo-Sanchez, David Fuentes-Jimenez, Cristina Losada-Gutierrez, Daniel Pizarro, Adrien Bartoli

“…WS-DeepSfT addresses the limitations of existing SfT techniques by combining a weakly-supervised deep neural network (DNN) for registration and a classical As-Rigid-As-Possible (ARAP) algorithm for 3D reconstruction. …”
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Intelligent Vision-Enabled Detection of Water-Surface Targets for Video Surveillance in Maritime Transportation by Yongqi Guo, Yuxu Lu, Yu Guo, Ryan Wen Liu, Kwok Tai Chui

“…To alleviate these limitations, we first investigate the influences of visibility enhancement methods on detection results and then propose a neural network-empowered water-surface target detection framework. …”
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Multi‐Wound Classification: Exploring Image Enhancement and Deep Learning Techniques by Prince Odame, Maxwell Mawube Ahiamadzor, Nana Kwaku Baah Derkyi, Kofi Agyekum Boateng, Kelvin Sarfo‐Acheampong, Eric Tutu Tchao, Andrew Selasi Agbemenu, Henry Nunoo‐Mensah, Dorothy Araba Yakoba Agyapong, Jerry John Kponyo

“…The approaches used included Contrast Limited Adaptive Histogram Equalization (CLAHE) with machine and deep learning models, Discrete Wavelet Transformations (DWT) with a novel Gated Wavelet Convolutional Neural Network (CNN) model, and FixCaps, an improved version of Capsule Networks utilizing Convolutional Block Attention Module (CBAM) to reduce spatial information loss. …”
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Skin Lesion Image Segmentation Algorithm Based on MC-UNet by Guihua Yang, Bingxing Pan

“…Aiming at the situation of dermatoscopic images with fuzzy lesion boundaries, variable morphology and high similarity to background, this paper proposes a skin lesion segmentation algorithm that achieves higher segmentation accuracy by combining existing convolutional neural network methods. The algorithm begins by using a Multiscale Residual Block (MRB) with different-sized convolutional kernels to enlarge the receptive field and extract multi-scale features of dermatoscopic images. …”
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Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission by Sandeep Sachdeva, Maninder Singh, U. P. Singh, Ajat Shatru Arora

“…To reduce the error of load forecasting, fuzzy method has been used with Artificial Neural Network (ANN) and OFDM transmission is used to get data from outer world and send outputs to outer world accurately and quickly. …”
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Research on the evaluation method of cooperative jamming effectiveness based on IPSO-ELM by A. Tianjian Yang, B. Xing Wang, C. Siyi Cheng, D. You Chen, E. Xi Zhang

“…On this basis, the cooperative jamming decision schemes and their corresponding cooperative jamming effectiveness values are solved at different locations in the target space, and the results are detected as outliers using box plots, thus constructing sample data for cooperative jamming effectiveness evaluation. Subsequently, a neural network based on the extreme learning machine methodology is developed, with its initial weights and biases fine-tuned through an improved particle swarm optimization, which is termed IPSO-ELM. …”
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Rapid Fluid Velocity Field Prediction in Microfluidic Mixers via Nine Grid Network Model by Qian Li, Yuwei Chen, Taotao Sun, Junchao Wang

“…Using this theory, we developed and trained an artificial neural network (ANN) to predict the fluid dynamics within microfluidic mixers. …”
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