Multi-Dimensional Feature Fusion and Enhanced Attention Streaming Movie Prediction Algorithm by Hanqing Hu, Tianmu Tian, Chengjing Liu, Xueyuan Bai

“…These features were combined with a long- and short-term memory network to explore their internal correlations. …”
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StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification by Muhammad Attique Khan, Muhammad Shahzad Sarfraz, Majed Alhaisoni, Abdulaziz A. Albesher, Shuihua Wang, Imran Ashraf

“…The proposed method is evaluated on a combined database. It accomplished an accuracy of 99.46%, which shows significant improvement over preceding techniques and other neural network architectures.…”
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Multispectral Target Detection Based on Deep Feature Fusion of Visible and Infrared Modalities by Yongsheng Zhao, Yuxing Gao, Xu Yang, Luyang Yang

“…Firstly, the YOLOv5 architecture is redesigned into a two-stream backbone network, incorporating a midway fusion strategy to integrate multimodal features from the C3 to C5 layers, thereby enhancing detection accuracy and robustness. …”
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A novel recommender system using light graph convolutional network and personalized knowledge-aware attention sub-network by Rasoul Hassanzadeh, Vahid Majidnezhad, Bahman Arasteh

“…Abstract Recently, graph neural networks (GNNs) have gained prominence in recommender systems (RS) due to their capability to extract vital features and understand intricate relationships. …”
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Algorithm for Recognition of Small Air Targets by Trajectory Features in Passive Bistatic Radar by Dao Van Luc, A. A. Konovalov, Le Minh Hoang

“…Development of an algorithm for recognizing small air targets by trajectory features based on machine learning. Implementation and evaluation of the quality of decision-making methods in a given recognition problem.   …”
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WinMRSI: Feature Matching With Window Attention for Multimodal Remote Sensing Image by Yide Di, Yun Liao, Yunan Liu, Hao Zhou, Kaijun Zhu, Mingyu Lu, Qing Duan, Junhui Liu

“…In addition, a dual-branch network is designed to capture contextual dependencies while refining local feature representations. …”
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DMFFNet: Dual-Mode Multiscale Feature Fusion-Based Pedestrian Detection Method by Ruizhe Hu, Ting Rui, Yan Ouyang, Jinkang Wang, Qunyan Jiang, Yinan Du

“…To address this problem, we propose a dual-modal multi-scale feature fusion network (DMFFNet). First, we use the MobileNet v3 backbone network to extract the features of dual-modal images as input for the multi-scale fusion attention (MFA) module, combining the idea of multi-scale feature fusion and attention mechanism. …”
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Interpreting CNN models for musical instrument recognition using multi-spectrogram heatmap analysis: a preliminary study by Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

“…The NSynth database was used for training and evaluation. Visual heatmap analysis and statistical metrics, including Difference Mean, KL Divergence, JS Divergence, and Earth Mover’s Distance, were utilized to assess feature importance and model interpretability.ResultsOur findings highlight the strengths and limitations of each spectrogram type in capturing distinctive features of different instruments. …”
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Epigenome profiling reveals distinctive regulatory features and cis-regulatory elements in pepper by Hongji Yang, Guorong Yu, Zhidong Lv, Tonghui Li, Xi Wang, Ying Fu, Zhangsheng Zhu, Guangjun Guo, Hang He, Ming Wang, Guochen Qin, Feng Liu, Zhenhui Zhong, Yan Xue

“…We generate stress responsive expression networks composed of potential transcription activators and their target genes. …”
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Deep Learning with Dual-Channel Feature Fusion for Epileptic EEG Signal Classification by Bingbing Yu, Mingliang Zuo, Li Sui

“…Channel 2 employs a dual-branch convolutional neural network (CNN) to extract deeper and distinct features. …”
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OPTICALS: A Novel Framework for Optimizing Predictive Trading Indicators in Cryptocurrency Using Advanced Learning Simulations by Hasib Shamshad, Fasee Ullah, Syed Adeel Ali Shah, Muhammad Faheem, Beena Shamshad

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Multiview Multimodal Feature Fusion for Breast Cancer Classification Using Deep Learning by Sadam Hussain, Mansoor Ali Teevno, Usman Naseem, Daly Betzabeth Avendano Avalos, Servando Cardona-Huerta, Jose Gerardo Tamez-Pena

“…Various augmentation techniques are applied to both imaging and textual data to expand the training dataset size. Imaging features were extracted using a Squeeze-and-Excitation (SE) network-based ResNet50 model, while textual features were extracted using an artificial neural network (ANN). …”
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Aeroengine Remaining Life Prediction Using Feature Selection and Improved SE Blocks by Hairui Wang, Shijie Xu, Guifu Zhu, Ya Li

“…To reduce computational costs and improve prediction performance, we use random forest to evaluate the feature importance of sensor data. Based on the size of the feature corresponding to the Gini index, we select the appropriate sensor. …”
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Multi-source image feature extraction and segmentation techniques for karst collapse monitoring by Wenbo Lin, Xiao Li, Tingting Li

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Skin Lesion Diagnosis Through Deep Learning and Hybrid Texture Feature Augmentation by Irpan Adiputra Pardosi, Roni Yunis, Arwin Halim

“…The framework integrates handcrafted features with Convolutional Neural Networks (CNNs) to enhance classification accuracy. …”
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Application of big data technology in visitor behavioral characteristics identification and energy efficiency assessment of intelligent scenic spots by Wei Zhou, Jin Cui

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Characterization of Wi-Fi Access Point Energy Consumption and the Impact of IEEE 802.11 Standard Evolutions by Hamidou Dembele

“…Addressing existing gaps in the literature, we first provide practical guidance for network engineers on how parameters such as transmit power, communication bandwidth, and standard evolution affect AP energy usage. …”
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Multi-granularity feature intersection learning for visible-infrared person re-identification by Sixian Chan, Jie Wang, Jiaao Cui, Jie Hu, Zhuorong Li, Jiafa Mao

“…Abstract This paper proposes a multi-granularity feature intersection network (MGFINet) for visible-infrared person re-identification (VI-ReID). …”
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Exploring unsupervised feature extraction algorithms: tackling high dimensionality in small datasets by Hongqi Niu, Gabrielle B. McCallum, Anne B. Chang, Khalid Khan, Sami Azam

“…In this regard, feature extraction algorithms are important in addressing these challenges by reducing dimensionality while retaining essential information. …”
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Automated Root Cause Analysis of Network Failures in IP/MPLS Network Using Machine Learning and Case-Based Reasoning by Tikumporn Wankvar, Apichon Witayangkurn

“…Managing IP/MPLS networks requires advanced tools due to their inherent complexity. …”
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