Brain Tumour Detection Using VGG-Based Feature Extraction With Modified DarkNet-53 Model by S. Trisheela, Roshan Fernandes, Anisha P. Rodrigues, S. Supreeth, B. J. Ambika, Piyush Kumar Pareek, Rakesh Kumar Godi, G. Shruthi

“…Artificial intelligence extends beyond pattern recognition, planning, and problem-solving, particularly in the realm of machine learning, where deep learning frameworks play a pivotal role. …”
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Unsupervised domain adaptation multi-level adversarial network for semantic segmentation based on multi-modal features by Zeyu WANG, Shuhui BU, Wei HUANG, Yuanpan ZHENG, Qinggang WU, Huawen CHANG, Xu ZHANG

“…In order to solve the problem of the distribution differences of visual, spatial, and semantic features between domains in domain adaptation, an unsupervised domain adaptation multi-level adversarial network for semantic segmentation based on multi-modal features was proposed.Firstly, an attentive fusion semantic segmentation network with three-layer structure was designed to learn the above three types of features from the source domain and target domain, respectively.Secondly, a self-supervised learning method jointing distribution confidence and semantic confidence was introduced into the single-level adversarial learning, so as to achieve the distribution alignment of more target domain pixels in the process of minimizing the distribution distance of the learnt features between domains.Finally, three adversarial branches and three adaptive sub-networks were jointly optimized by the multi-level adversarial learning method based on multi-modal features, which could effectively learn the invariant representation between domains for the features extracted from each sub-network.The experimental results show that compared with existing state-of-the-art methods, on the datasets of GTA5 to Cityscapes, SYNTHIA to Cityscapes, and SUN-RGBD to NYUD-v2 the proposed network achieves the best mean intersection over union of 62.2%, 66.9%, and 59.7%, respectively.…”
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An Explainable Deep Learning Network for Environmental Microorganism Classification Using Attention-Enhanced Semi-Local Features by R. Karthik, Armaano Ajay, Akshaj Singh Bisht, Jaehyuk Cho, V. E. Sathishkumar

“…The DenseNet-169 architecture is modified to integrate the EHCR and DASA blocks, allowing the model to focus on semi-local feature extraction for improved feature representation. …”
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Improving Generalization of Genetic Programming for High-Dimensional Symbolic Regression with Shapley Value Based Feature Selection by Chunyu Wang, Qi Chen, Bing Xue, Mengjie Zhang

“…Abstract Symbolic Regression (SR) on high-dimensional datasets often encounters significant challenges, resulting in models with poor generalization capabilities. While feature selection has the potential to enhance the generalization and learning performance in general, its application in Genetic Programming (GP) for high-dimensional SR remains a complex problem. …”
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Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

“…The model uses a wrapper-based feature selection technique using machine learning algorithms to select the best features, which are then combined and fed into a Multi-Head Attention-based transformer for getting the predictions. …”
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Multi-objective: hybrid particle swarm optimization with firefly algorithm for feature selection with Leaky ReLU by Ashish Kumar Singh, Anoj Kumar

“…Abstract High-dimensional datasets often pose challenges due to the presence of numerous irrelevant and redundant features, which can compromise the performance of machine learning models. …”
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Research on Space Targets Simulation Modulation Algorithm Combined Global–Local Multi-Spectral Radiation Features by Yu Zhang, Songzhou Yang, Zhipeng Wei, Jian Zhang, Bin Zhao, Dianwu Ren, Jingrui Sun, Lu Wang, Taiyang Ren, Dongpeng Yang, Guoyu Zhang

“…To solve the international problem of global–local radiation features simulation of multi-spectral space targets, this paper proposes a multi-spectral space target simulation modulation algorithm that can combine global–local spectral radiation features. …”
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LEGAL BASIS AND SPECIFIC FEATURES OF FEDERAL INSTITUTIONS OF PUBLIC HEALTH REORGANIZATION ACCORDING TO RUSSIAN CIVIL LEGISLATION by Oleg E. Karpov, Irina V. Fadeeva, Dmitriy N. Nikitenko, Victor V. Tretyakov, Ekaterina M. Nushtaeva

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Ontogenetic features of <I>Saposhnikovia divaricate</I> (Turcz.) Schischk. introduced into the environments of the Cis-Baikal Region by E. G. Khudonogova, S. V. Polovinkina

“…Plant introduction studies can solve the problem of sustainable utilization and conservation of the species.Materials and methods. …”
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A method for identifying gully-type debris flows based on adaptive multi-scale feature extraction by Qiuyu Liu, Ting Wang, Zhijie Zheng, Baoyun Wang

“…Integrated into the feature layer of Convolutional Neural Network (CNN) to solve the multi-scale feature extraction problem of gullies. …”
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Hierarchical Multi-Scale Patch Attention and Global Feature-Adaptive Fusion for Robust Occluded Face Recognition by Elhamsadat Hejazi, Majid Ahmadi, Arash Ahmadi

“…Occluded face recognition remains a challenging problem in biometric identification, where real-world obstructions such as masks, sunglasses, scarves, and hands obscure key facial features. …”
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Single-Character-Based Embedding Feature Aggregation Using Cross-Attention for Scene Text Super-Resolution by Meng Wang, Qianqian Li, Haipeng Liu

“…In this paper, we propose single-character-based embedding feature aggregation using cross-attention for scene text super-resolution (SCE-STISR) to solve this problem. …”
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Networking of Smart Meters Based on Time-Varying Feature of Low-Voltage Power Line Channel in Microgrid by Ya-Xin Huang, Xiao-Di Zhang, Fei Yu, Yong-Qing Wei, Hai-Long Zhang

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Nosocomial <i>Klebsiella pneumoniae</i> infection in a cardiac surgery hospital: clinical and microbiological features by M. V. Kuznetsova, V. S. Mihailovskaya, L. G. Kudryavtseva, V. I. Sergevnin

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Comprehensive Feature-Driven PCOS Predictor: A Reinforcement Learning-Based Binary Equilibrium Optimization Approach by S. Reka, T. Suriya Praba, Krishna Kumar Manchala, Anna Venkateswarlu

“…Then, Reinforcement Learning-based Binary Equilibrium Optimizer is used to find the reduced optimal features. Here, RL uses SARSA (State–Action–Reward–State–Action) to increase the population diversity in the search space, to avoid the problem of local optima, finally balances the exploration capability during the search. …”
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MSF-SLAM: Enhancing Dynamic Visual SLAM with Multi-Scale Feature Integration and Dynamic Object Filtering by Yongjia Duan, Jing Luo, Xiong Zhou

“…At the core of our approach lies a novel Multi-Scale Feature Consolidation (MSFConv) module, which we have developed to significantly boost the feature extraction capabilities of the YOLOv8 network. …”
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Improving Gaussian Naive Bayes classification on imbalanced data through coordinate-based minority feature mining by Wei Wang, Li Yan, Fen Liu, Yanxi Li

“…The algorithm transforms the dataset from absolute coordinates to RLDC-relative coordinates, revealing latent local relative density change features. Due to the imbalanced distribution, sparse feature space, and class overlap, minority class samples can exhibit distinct patterns in these transformed features. …”
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A Study on the STGCN-LSTM Sign Language Recognition Model Based on Phonological Features of Sign Language by Yuxin Han, Yong Han, Qi Jiang

“…Many isolated words in Chinese Sign Language (CSL) exhibit significant feature similarities, which are primarily conveyed through hand, face, and body movements. …”
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A novel multimodal image feature fusion mechanism: Application to rabbit liveweight estimation in commercial farms by Daoyi Song, Zhenhao Lai, Shuqi Yang, Dongyu Liu, Jinxia (Fiona) Yao, Hongying Wang, Liangju Wang

“…Specifically, a dual-stream feature fusion mechanism was proposed to effectively integrate information from both near-infrared and depth imaging. …”
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Robust Registration of Multimodal Remote Sensing Images Using Self-Similar Adjacent Self-Convolutional Feature by Tian Gao, Chaozhen Lan, Liang Lv, Qunshan Shi, Wenjun Huang, Yiqiao Wang, Zhizhen Mu

“…., optical, infrared, SAR), image registration remains a challenging problem. This article proposes a robust matching method based on self-similarity adjacent self-convolution features (SASF), consisting of two key steps. …”
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