Foreground and Background Interaction Fusion Network for Camouflaged Object Detection by WEI Mingjun, LIU Ming, LIU Yazhi, LI Hui

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Aggregated Time Series Features in a Voxel-Based Network Architecture by Zsolt Vincze, Andras Rovid

“…During the evaluation, the authors examine the object detection performance of a popular voxel-based neural network with its original architecture and several variants where the time domain related features were propagated through the network and aggregated at different stages of processing. …”
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Network of Settlements in Novosibirsk District in 1920s: Population, Structure and Development Features by A. I. Tatarnikova

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Graph Attention Neural Network Model With Behavior Features for Knowledge Tracking by Wei Zhang, Sen Hu, Kaiyuan Qu

“…In order to solve the above problems, a graph attention neural network model with behavior features for knowledge tracking (GAKT-BF) is proposed in this paper. …”
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Evaluation of initial geostress field of underground powerhouse in the complex alteration area of western Sichuan based on back-propagation neural network method by Hong Zheng, Shiqi Cao, Quan Jiang, Shaojun Li, Dingping Xu, Zhiwei Li

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General model for best feature extraction of EEG using discrete wavelet transform wavelet family and differential evolution by Ahmad al-Qerem, Faten Kharbat, Shadi Nashwan, Staish Ashraf, khairi blaou

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Deep blur detection network with boundary-aware multi-scale features by Xiaoli Sun, Qiwei Wang, Xiujun Zhang, Chen Xu, Weiqiang Zhang

“…To solve this problem, we newly establish a boundary-aware multi-scale deep network in this paper. First, the VGG-16 network is used to extract the deep features from multi-scale layers. …”
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Improving multi-talker binaural DOA estimation by combining periodicity and spatial features in convolutional neural networks by Reza Varzandeh, Simon Doclo, Volker Hohmann

“…Abstract Deep neural network-based direction of arrival (DOA) estimation systems often rely on spatial features as input to learn a mapping for estimating the DOA of multiple talkers. …”
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The Fruit Recognition and Evaluation Method Based on Multi-Model Collaboration by Mingzheng Huang, Dejin Chen, Dewang Feng

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Power Metal Corrosion Evaluation Method Based on Image Feature Analysis by ZHONG Yao, ＲEN Xiao, WU Gao-lin, WANG Qian, WANG Xu-peng, HAO Jian

“…First，multi-dimensional feature parameters were extracted through image preprocessing，chromatics，statistics， wavelet and fractal analysis methods; then，a metal corrosion state evaluation method was proposed based on neural network algorithm，and the effectiveness of the method was verified. …”
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LSTM Logging Curve Prediction Method Based on Attention Mechanism by DAI Baoqing, PENG Jiaqiong, ZHANG Tianhuan, ZHAO Jiafeng, ZHAO Jianpeng

Subjects: “…log evaluation…”
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Distribution and Evolution of Chorus Waves Modeled by a Neural Network: The Importance of Imbalanced Regression by Xiangning Chu, Jacob Bortnik, Wen Li, Xiao‐Chen Shen, Qianli Ma, Donglai Ma, David Malaspina, Sheng Huang

“…Using an imbalanced regressive (IR) method, we develop a neural network model of lower‐band (LB) chorus waves using 7‐year observations from the EMFISIS instrument onboard Van Allen Probes. …”
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An evolution model for urban rail transit hyper networks based on allometric growth relationship by Zehua Zhang, Ruining Wei, Shumin Feng, Lei Xu, Fan Yang, Hao Liu, Yiqiang Jiang

“…Empirical validation using subway network data from Beijing, Shanghai, and Guangzhou (222–378 stations) was conducted via Python simulations, with model efficacy evaluated through Kolmogorov-Smirnov (K-S) tests and multi-index comparisons. …”
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High‐order multilayer attention fusion network for 3D object detection by Baowen Zhang, Yongyong Zhao, Chengzhi Su, Guohua Cao

“…By incorporating filtering and non‐linear activation, we extract deep semantic information from the fused multi‐modal features. To maximize the effectiveness of the fused salient feature information, we introduce an attention mechanism that dynamically evaluates the importance of pooled features at each level, enabling adaptive weighted fusion of significant and secondary features. …”
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Agricultural Cultivation Cost Prediction Using Neural Networks and Feature Importance Analysis by Salmania Putri, Tora Fahrudin, Asti Widayanti

“…This research aims to achieve high productivity in the agricultural sector by using neural networks or Deep Learning methods to predict the cost of agricultural cultivation, as well as identifying significant factors that affect the profitability of potato commodities with Feature Importance analysis. …”
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An Effective Network Intrusion Detection System Using Recursive Feature Elimination Technique by Narendra Singh Yadav, Vijay Prakash Sharma, D. Sikha Datta Reddy, Saswati Mishra

“…These systems are proposed to identify and classify cyber-attacks on the network. However, an exhaustive assessment and performance evolution of various machine learning algorithms remains unavailable. …”
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Network Data Plane Programming Languages: A Survey by Belén Brandino, Eduardo Grampín

“…Network data plane programming is a consequence of the evolution of the concept of control and data plane separation, stated two decades ago, and established on the Software-Defined Networking (SDN) architecture. …”
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FGBNet: A Bio-Subspecies Classification Network with Multi-Level Feature Interaction by Yang Yuan, Danping Huang, Bingbin Cai, Yang Shen, Jingdan Wang, Jiale Xv, Siyu Chen

“…Through experimentation and optimization, the ConvNeXt is selected as the backbone network for FGBNet feature extraction, and the effectiveness of the multi-level feature interaction method is verified. …”
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Liver segmentation network based on detail enhancement and multi-scale feature fusion by Lu Tinglan, Qin Jun, Qin Guihe, Shi Weili, Zhang Wentao

“…Through the aforementioned research, this paper proposes a liver segmentation network based on detail enhancement and multi-scale feature fusion (DEMF-Net). …”
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A Lightweight Tri-Stream Feature Fusion Network for Speech Emotion Recognition by Ronghe Cao, Yunxing Wang, Xiaolong Wu, Shuang Jin, Huiling Niu

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