On OCT Image Classification via Deep Learning by Depeng Wang, Liejun Wang

“…In this paper, an automatic method based on deep learning is proposed to detect AME and AMD lesions, in which two publicly available OCT datasets of retina were adopted and a network model with effective feature of reuse feature was applied to solve the problem of small datasets and enhance the adaptation to the difference of different datasets of the approach. …”
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Validation of the Social Mistrust Scale in non-clinical and clinical samples of children aged 8–14 years living in Italy: convergence with anxiety and depression by Valerio Zaccaria, Francesco Pisani, Keri Ka-Yee Wong, Ignazio Ardizzone, Susanna Maggi, Federica Forte, Emiliano Luchetti, Elvira Piazza, Chiara Rogora

“…Background Paranoia exists in the general population, both in adults and in children, and is a key feature of schizotypy and schizophrenia-spectrum disorders. …”
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The development of the generative adversarial supporting vector machine for molecular property generation by Qing Lu

“…In addition, each generated feature vector is unique, so the mode collapse problem is avoided, which is often encountered in the GAN model. …”
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TGF-Net: Transformer and gist CNN fusion network for multi-modal remote sensing image classification. by Huiqing Wang, Huajun Wang, Linfen Wu

“…This enables the extraction of distinct as well as common features. Meanwhile, the transformer-based spectral feature extraction module (TSFEM) was designed by combining the different characteristics of remote sensing images and considering the problem of orderliness of the sequence between hyperspectral image (HSI) channels. …”
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Crack fault diagnosis of vibration exciter rolling bearing based on genetic algorithm–optimized Morlet wavelet filter and empirical mode decomposition by Xiaoming Han, Jin Xu, Songnan Song, Jiawei Zhou

“…To solve this problem, a fault feature recognition method based on genetic algorithm–optimized Morlet wavelet filter and empirical mode decomposition is proposed. …”
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基于MED-SVM的齿轮箱故障诊断方法 by 刘志川, 唐力伟, 曹立军, 张远刚

“…In order to solve the problem of gearbox fault diagnosis,a new method based on minimum entropy deconvolution（MED）and support vector machine（SVM）is proposed.MED is used for gearbox vibration acceleration signal under background noise,then feature parameters extracted on breadth domain,frequency domain and energy domain of decreased signal are carried out,and the feature vector is built.Taking the feature vector as input,the multi-classification support vector machine is established,and the model parameters optimized by cross validation method are used to identify gearbox fault types.The fault diagnosis result of practical gearbox vibration signals shows that the proposed method can effectively identify different fault types of gear and bearing,and the optimizing model parameters can evidently improve fault identification accuracy.…”
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Projectile Explosion Weak Firelight Image Recognition Method Using Multi-Scale Adaptive Enhancement Network by Xuebin Liu, Hanshan Li, Shaopeng Liang

“…The traditional VGG16 backbone network is used as the feature extraction network, and the firelight feature extraction network structure of the projectile explosion image is designed by adding the bidirectional aggregation feature pyramid. …”
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A Satellite Navigation Spoofing Interference Detection Method Based on LSTM by ZHAO Shen, HUANG Wenna, QIN Yemei, LIAO Yifei, YANG Lingling

“…Facing the problem of satellite navigation spoofing interference detection, this paper proposes a feature parameter selection and data processing method applicable to the detection of spoofing interference by Long Short-term Memory (LSTM) neural network. …”
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DDoS attack detection method based on improved convolutional long short-term memory and three-way decision in SDN. by Haizhen Wang, Xiaojing Yang, Na Jia

“…It is based on the Convolutional Long Short-Term Memory Network (ConvLSTM) and three-way decision (TWD). It solves the problem of insufficient feature extraction in SDN environment and improves classification accuracy. …”
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Imbalanced Power Spectral Generation for Respiratory Rate and Uncertainty Estimations Based on Photoplethysmography Signal by Soojeong Lee, Mugahed A. Al-antari, Gyanendra Prasad Joshi, Yeong Hyeon Gu

“…Hence, we apply ML models by mixing artificial feature curves generated using a bootstrap model with the original feature curves to estimate RRs and solve this problem. …”
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FUR-DETR: A Lightweight Detection Model for Fixed-Wing UAV Recovery by Yu Yao, Jun Wu, Yisheng Hao, Zhen Huang, Zixuan Yin, Jiajing Xu, Honglin Chen, Jiahua Pi

“…Secondly, an adaptive multiscale feature pyramid network (AMFPN) is designed, which effectively integrates different scales of information through multi-level feature fusion and information transmission mechanism, alleviates the problem of information loss in small-target detection, and improves the detection accuracy in complex backgrounds. …”
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Approach to Semantic Visual SLAM for Bionic Robots Based on Loop Closure Detection with Combinatorial Graph Entropy in Complex Dynamic Scenes by Dazheng Wang, Jingwen Luo

“…First, in terms of the dynamic feature detection results of YOLOv8-seg, the feature points at the edges of the dynamic object are finely judged by calculating the mean absolute deviation (MAD) of the depth of the pixel points. …”
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Application of a sEMG hand motion recognition method based on variational mode decomposition and ReliefF algorithm in rehabilitation medicine. by Yue Yuan

“…Next, the ReliefF algorithm is used to remove redundant features from the feature space. In order to select a feature space that can effectively reflect the intention of hand movements, the hand movement recognition performance of 8 low-dimensional feature spaces is evaluated. …”
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A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling by Jingyu Zhou, Shulin Tian, Chenglin Yang

“…To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. …”
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A cascaded autoencoder unmixing network for Hyperspectral anomaly detection by Kun Li, Yingqian Wang, Qiang Ling, Yaoming Cai, Yao Qin

“…However, since abundance feature extraction and anomaly detection are decoupled, the learned features are not well-suitable for the subsequent detection. …”
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MalGEA: A malware analysis framework via matrix factorization based node embedding and graph external attention by Ruisheng Li, Qilong Zhang, Huimin Shen

“…In recent years, researchers have proposed a number of graph representation learning based malware detection methods by leveraging the intrinsic topological features of malware, which has led to considerable development in this area. …”
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A Real-Time Capable Dynamic Partial Reconfiguration System for an Application-Specific Soft-Core Processor by Michael Kirchhoff, Philipp Kerling, Detlef Streitferdt, Wolfgang Fengler

“…In this paper, a novel method that addresses this problem is introduced, and its realization is described. …”
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Cross-Modal Complementarity Learning for Fish Feeding Intensity Recognition via Audio–Visual Fusion by Jian Li, Yanan Wei, Wenkai Ma, Tan Wang

“…To address these problems, we propose the Adaptive Cross-modal Attention Fusion Network (ACAF-Net), a cross-modal complementarity learning framework with a two-stage attention fusion mechanism: (1) a cross-modal enhancement stage that enriches individual representations through Low-rank Bilinear Pooling and learnable fusion weights; (2) an adaptive attention fusion stage that dynamically weights acoustic and visual features based on complementarity and environmental reliability. …”
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A TEI Customization for Writing TEI Customizations by Syd Bauman

“…A schema, in general, is intended to be used to check a document for errors before those errors cause problems in processing. However, schemas can also help us write our documents. …”
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An Efficient Model for Leafy Vegetable Disease Detection and Segmentation Based on Few-Shot Learning Framework and Prototype Attention Mechanism by Tong Hai, Yuxin Shao, Xiyan Zhang, Guangqi Yuan, Ruihao Jia, Zhengjie Fu, Xiaohan Wu, Xinjin Ge, Yihong Song, Min Dong, Shuo Yan

“…This study proposes a model for leafy vegetable disease detection and segmentation based on a few-shot learning framework and a prototype attention mechanism, with the aim of addressing the challenges of complex backgrounds and few-shot problems. Experimental results show that the proposed method performs excellently in both object detection and semantic segmentation tasks. …”
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