TransFINN “Transparent Feature Integrated Neural Network for Text Feature Selection and Classification” by Saif Ur Rehman, Ramsha Jat, Muhammad Rafi, Jaroslav Frnda

“…This paper introduces TransFINN, a transparent extension artificial neural network that combines transparent feature selection with text classification. …”
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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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Features of digital management of modern economy by F. F. Sharipov, M. A. Dyakonova, M. Xu

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Optimized driver fatigue detection method using multimodal neural networks by Shengli Cao, Peihua Feng, Wei Kang, Zeyi Chen, Bo Wang

“…Two advanced neural network models were developed and evaluated: a multimodal feature combination model and a multimodal feature coupled model. …”
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Evaluating Feature Impact Prior to Phylogenetic Analysis Using Machine Learning Techniques by Osama A. Salman, Gábor Hosszú

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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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Network-Based Hierarchical Feature Augmentation for Predicting Road Classes in OpenStreetMap by Müslüm Hacar, Diego Altafini, Valerio Cutini

“…Addressing this challenge, our research introduces a novel hierarchical feature augmentation approach to developing machine learning classifiers by the features retrieved from various levels of road network connectivity. …”
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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…Motivated by this, we propose a multi-resolution scale feature fusion-based universal density counting network (MRSNet). …”
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A quantitative benchmark of neural network feature selection methods for detecting nonlinear signals by Antoine Passemiers, Pietro Folco, Daniele Raimondi, Giovanni Birolo, Yves Moreau, Piero Fariselli

“…We also use the same settings to benchmark the reliability of gradient-based feature attribution techniques for Neural Networks (NNs), such as Saliency Maps (SM). …”
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Interpretable capsule networks via self attention routing on spatially invariant feature surfaces by Peizhang Li, Jiyuan Ru, Qing Fei, Zhen Chen, Bo Wang

“…However, current classification approaches based on convolutional neural networks often suffer from limited generalization and robustness, particularly when processing data characterized by abstract class features and pronounced spatial attributes. …”
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Dynamic Bidirectional Feature Enhancement Network for Thin Cloud Removal in Remote Sensing Images by Yu Wang, Hao Chen, Ye Zhang, Guozheng Li

“…To address these issues, we propose a dynamic bidirectional feature enhancement network for thin cloud removal in optical remote sensing images. …”
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Application of Generative Adversarial Networks Based on Global and Local Feature Information in Hippocampus Segmentation by WEI Zhihong, KONG Xudong, KONG Yan, YAN Shiju, DING Yang, WEI Xianding, KONG Dong, YANG Bo

“…To address this issue, this study proposes a generative adversarial network (GAN) based on global and local feature information (GLGAN) for hippocampus segmentation. …”
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Copy-Move Forgery Detection Technique Using Graph Convolutional Networks Feature Extraction by Varun Shinde, Vineet Dhanawat, Ahmad Almogren, Anjanava Biswas, Muhammad Bilal, Rizwan Ali Naqvi, Ateeq Ur Rehman

“…This paper presents a new method for CMF Detection (CMFD) that uses the power of Graph Convolution Networks (GCNs) and its multiple layers with ReLU activation, for CMFD and analysis. …”
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Transfer learning based feature selection for feedforward neural network for speech emotion classifier by D. V. Krasnoproshin, M. I. Vashkevich

“…Proposed transfer learning approach consist in employing the backward-step selection algorithm for feature selection using statistical learning classifiers, the obtained subset of features than subsequently used to train feedforward neural networks. …”
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A music structure analysis method based on beat feature and improved residual networks. by Bing Lu, Qianxue Zhang, Yi Guo, Fuqiang Hu, Xuejun Xiong

“…In response to the issues of insufficient audio feature representation and insufficient model generalization ability in music structure analysis methods, a music structure analysis method based on beat feature fusion and an improved residual network was designed. …”
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Identifying Influential Nodes in Complex Networks via Transformer with Multi-Scale Feature Fusion by Tingshuai Jiang, Yirun Ruan, Tianyuan Yu, Liang Bai, Yifei Yuan

“…Through the transformer module, node information is effectively aggregated, thereby improving the model’s ability to recognize key nodes. We perform evaluations using six real-world and three synthetic network datasets, comparing our method against multiple baselines using the SIR model to validate its effectiveness. …”
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AEFFNet: Attention Enhanced Feature Fusion Network for Small Object Detection in UAV Imagery by Zhaoyu Nian, Wenzhu Yang, Hao Chen

“…Addressing the specific challenges posed by small and densely distributed objects in such images, we introduce an attention enhanced feature fusion network (AEFFNet) designed specifically for small object detection in UAV imagery. …”
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Network traffic anomaly detection model based on feature grouping and multi‐autoencoders integration by Yang Zhou, Haoyang Zeng, Zhourong Zheng, Wei Zhang

“…Abstract This paper presents a network traffic anomaly detection model based on feature grouping and multiple autoencoders (multi‐AEs) integration. …”
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Terrain and Atmosphere Classification Framework on Satellite Data Through Attentional Feature Fusion Network by Antoni Jaszcz, Dawid Połap

“…Hence, in this paper, we propose a neural classifier architecture that analyzes different features by the parallel processing of information in the network and combines them with a feature fusion mechanism. …”
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A lightweight remote sensing image detection model with feature aggregation diffusion network by Xiaohui Cheng, Xukun Wang, Yun Deng, Qiu Lu, Yanping Kang, Jian Tang, Yuanyuan Shi, Junyu Zhao

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