Human motion similarity evaluation based on deep metric learning by Yidan Zhang, Lei Nie

“…Specifically, when extracting the action information feature vectors using the automatic encoder-decoder network model, a sliding window method is used to divide the key point sequences of each limb part into sequence patches, and the action information feature vectors independent of the camera viewpoint and skeleton structure are extracted in a smaller time unit, so as to obtain a more refined action similarity evaluation result. …”
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Enhanced Grey Wolf Optimization (EGWO) and random forest based mechanism for intrusion detection in IoT networks by Saad Said Alqahtany, Asadullah Shaikh, Ali Alqazzaz

“…The selected features are evaluated by using the Random Forest (RF) algorithm to combine multiple decision trees and create an accurate result. …”
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Recognition of Sheep Feeding Behavior in Sheepfolds Using Fusion Spectrogram Depth Features and Acoustic Features by Youxin Yu, Wenbo Zhu, Xiaoli Ma, Jialei Du, Yu Liu, Linhui Gan, Xiaoping An, Honghui Li, Buyu Wang, Xueliang Fu

“…The method included evaluating and filtering the optimal acoustic features, utilizing a customized convolutional neural network (SheepVGG-Lite) to extract Short-Time Fourier Transform (STFT) spectrograms and Constant Q Transform (CQT) spectrograms’ deep features, employing cross-spectrogram feature fusion and assessing classification performance through a support vector machine (SVM). …”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…The proposed approach begins with feature extraction using ResNet50, a deep convolutional neural network known for its robust feature representation capabilities. …”
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Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail, Ahmet Sait Alali, Ahmad Muhammad, Mahmoud Ashraf, Sameh O. Abdellatif

“…This study introduces a novel figure of merit for evaluating the stability of perovskite solar cells (PSCs) by employing advanced Long Short-Term Memory (LSTM) neural networks to investigate degradation mechanisms. …”
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A Novel Framework for Improving Soil Organic Carbon Mapping Accuracy by Mining Temporal Features of Time-Series Sentinel-1 Data by Zhibo Cui, Bifeng Hu, Songchao Chen, Nan Wang, Defang Luo, Jie Peng

“…The performance of the partial least squares regression, random forest, and convolutional neural network–long short-term memory (CNN-LSTM) models was evaluated using a 10-fold cross-validation approach. …”
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spaMGCN: a graph convolutional network with autoencoder for spatial domain identification using multi-scale adaptation by Tianjiao Zhang, Hongfei Zhang, Zhongqian Zhao, Saihong Shao, Yucai Jiang, Xiang Zhang, Guohua Wang

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Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

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DeepAptamer: Advancing high-affinity aptamer discovery with a hybrid deep learning model by Xin Yang, Chi Ho Chan, Shanshan Yao, Hang Yin Chu, Minchuan Lyu, Ziqi Chen, Huan Xiao, Yuan Ma, Sifan Yu, Fangfei Li, Jin Liu, Luyao Wang, Zongkang Zhang, Bao-Ting Zhang, Lu Zhang, Aiping Lu, Yaofeng Wang, Ge Zhang, Yuanyuan Yu

“…To address these challenges, we proposed DeepAptamer for identifying high-affinity sequences from unenriched early SELEX rounds. As a hybrid neural network model combining convolutional neural networks and bidirectional long short-term memory, DeepAptamer integrated sequence composition and structural features to predict aptamer binding affinities and potential binding motifs. …”
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Deep Learning-Based Fingerprint–Vein Biometric Fusion: A Systematic Review with Empirical Evaluation by Sarah Almuwayziri, Abeer Al-Nafjan, Hessah Aljumah, Mashael Aldayel

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Application of BERT-GCN Model Based on Strong Link Relation Graph in Water Use Enterprise Classification by Junhong Xiang, Baoxian Zheng, Chenkai Cai, Shuiping Yao, Shang Gao

“…First, we constructed a co-word relation graph based on the typical industry characteristics keywords extracted by the <i>TF-IDF</i> and extracted co-word relation features using a graph convolutional network (GCN). …”
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Evaluating and Enhancing Face Anti-Spoofing Algorithms for Light Makeup: A General Detection Approach by Zhimao Lai, Yang Guo, Yongjian Hu, Wenkang Su, Renhai Feng

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MedFuseNet: fusing local and global deep feature representations with hybrid attention mechanisms for medical image segmentation by Ruiyuan Chen, Saiqi He, Junjie Xie, Tao Wang, Yingying Xu, Jiangxiong Fang, Xiaoming Zhao, Shiqing Zhang, Guoyu Wang, Hongsheng Lu, Zhaohui Yang

“…Although several impressive deep learning architectures based on convolutional neural networks (CNNs) and Transformers have recently demonstrated remarkable performance, there is still potential for further performance improvement due to their inherent limitations in capturing feature correlations of input data. …”
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A Cross-Fusion Network for Salient Object Detection in Optical Remote Sensing Images by Weining Zhai, Panpan Zheng, Liejun Wang

“…The post-aggregation reassignment block utilizes multiscale fusion and edge features generated by the edge detection network to enrich semantic and detailed information, effectively handling intricate details. …”
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Incorporated flexible load forecasting based on non-intrusive load monitoring: a TCN-based meta learning approach by Yun Zhang, Quanyan Shu, Feng Ding, Feng Liu, Shuiming Jiang, Wenlong Wu

“…Thirdly, a two-tiered learning process is implemented to adapt features from load disaggregation to forecasting.The efficacy of the proposed method is evaluated using public datasets, and the results demonstrate its superiority to baseline models in terms of forecasting accuracy for flexible loads. …”
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Computer-aided diagnosis of hepatic cystic echinococcosis based on deep transfer learning features from ultrasound images by Miao Wu, Chuanbo Yan, Gan Sen

“…The proposed CAD system adopts the concept of deep transfer learning and uses a pre-trained convolutional neural network (CNN) named VGG19 to extract deep CNN features from the ultrasound images. …”
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Modeling Upscaled Mass Discharge From Complex DNAPL Source Zones Using a Bayesian Neural Network: Prediction Accuracy, Uncertainty Quantification and Source Zone Feature Importance by Xueyuan Kang, Amalia Kokkinaki, Xiaoqing Shi, Jonghyun Lee, Zhilin Guo, Lingling Ni, Jichun Wu

“…We evaluated the proposed model on laboratory‐scale DNAPL dissolution experiments. …”
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Flow Field Reconstruction and Prediction of Powder Fuel Transport Based on Scattering Images and Deep Learning by Hongyuan Du, Zhen Cao, Yingjie Song, Jiangbo Peng, Chaobo Yang, Xin Yu

“…Based on the acquired scattering images, a prediction and reconstruction method was developed using a deep network framework composed of a Stacked Autoencoder (SAE), a Backpropagation Neural Network (BP), and a Long Short-Term Memory (LSTM) model. …”
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MRFB-Net: A Novel Attention Pooling Network With Modified Receptive Field Block for Uterine Fibroid Segmentation by Yun Jiang, Xiaokang Ding, Hongmei Zhou

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Peatland pixel-level classification via multispectral, multiresolution and multisensor data using convolutional neural network by Luca Zelioli, Fahimeh Farahnakian, Maarit Middleton, Timo P. Pitkänen, Sakari Tuominen, Paavo Nevalainen, Jonne Pohjankukka, Jukka Heikkonen

“…To address these challenges, we propose a novel multi-modal convolutional neural network (CNN) architecture designed specifically for pixel-level peatland classification. …”
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