Research on deep learning model for stock prediction by integrating frequency domain and time series features by Wenjie Sun, Jianhua Mei, Shengrui Liu, Chunhong Yuan, Jiaxuan Zhao

“…While temporal feature analysis is common, frequency-domain features, derived via spectral analysis (e.g., Fourier Transform), can reveal latent periodicities and seasonality patterns in price movements. …”
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UAV rice panicle blast detection based on enhanced feature representation and optimized attention mechanism by Shaodan Lin, Deyao Huang, Libin Wu, Zuxin Cheng, Dapeng Ye, Haiyong Weng

“…This design aims to enhance feature extraction and focus on critical image regions, addressing the challenges of detecting small and complex disease patterns in UAV-captured imagery. …”
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RETRACTED: THE PROBLEMS OF CLASSIFICATION AND SPECIFIC FEATURES OF MORPHOGENESIS OF GLANDS LOCATED IN THE WALLS OF HOLLOW INTERNAL ORGANS by M. P. Sapin, V. N. Nikolenko, D. B. Nikityuk, S. V. Chava

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A Dual-Branch Fusion Model for Deepfake Detection Using Video Frames and Microexpression Features by Georgios Petmezas, Vazgken Vanian, Manuel Pastor Rufete, Eleana E. I. Almaloglou, Dimitris Zarpalas

“…In this paper, we propose a novel approach to deepfake detection by combining video frame analysis with facial microexpression features. The dual-branch fusion model utilizes a 3D ResNet18 for spatiotemporal feature extraction and a transformer model to capture microexpression patterns, which are difficult to replicate in manipulated content. …”
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Advanced cloud intrusion detection framework using graph based features transformers and contrastive learning by Vijay Govindarajan, Junaid Hussain Muzamal

“…Abstract This paper presents a modular and scalable intrusion detection framework that combines graph-based feature extraction, Transformer-based autoencoding, and contrastive learning to improve detection accuracy in cloud environments. …”
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Interpretable Identification of Dynamic Adaptive Streaming over HTTP (DASH) Flows Based on Feature Engineering by Arkadiusz Biernacki

“…Our methodology involves feature generation, filtering, and clustering. The clustering used the most significant features to group similar traffic patterns. …”
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Network-based clustering unveils interconnected landscapes of genomic and clinical features across myeloid malignancies by Fritz Bayer, Marco Roncador, Giusi Moffa, Kiyomi Morita, Koichi Takahashi, Niko Beerenwinkel, Jack Kuipers

“…Abstract Myeloid malignancies exhibit considerable heterogeneity with overlapping clinical and genetic features among subtypes. We present a data-driven approach that integrates mutational features and clinical covariates at diagnosis within networks of their probabilistic relationships, enabling the discovery of patient subgroups. …”
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Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques by S. Vijayalakshmi, Binay Kumar Pandey, Digvijay Pandey, Mesfin Esayas Lelisho

“…These features are input into a 2D BiLSTM-CNN model designed to learn spatial and sequential patterns in mammogram images. …”
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Distribution of local curvature values as a structural feature for off-line handwritten signature verification by V. V. Starovoitov, U. Akhundjanov

“…When verifying a signature with N authentic signatures of the same person, N(N-1)/2 patterns of the proximity of pairs of genuine signatures and N images of pairs of proximity of the analyzed signature with genuine signatures are presented in the feature space. …”
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DMAC: Discovering Multi-Attribute Correlations of Deep Quality Features for Defect Detection in Mechanical Components by Yue Yu

“…This paper introduces DMAC (Discovering Multi-Attribute Correlations of Deep Quality Features), a novel framework that enhances defect detection in mechanical components by leveraging multimodal quality-guided deep/shallow feature fusion techniques. …”
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Recurrent features of amplitudes in planar N $$ \mathcal{N} $$ = 4 super Yang-Mills theory by Tianji Cai, François Charton, Kyle Cranmer, Lance J. Dixon, Garrett W. Merz, Matthias Wilhelm

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The impact of social features on the financial sustainability of pension systems in Central and Eastern Europe and Baltic States by Florin Cornel Dumiter, Klaus Bruno Schebesch, Ștefania Amalia Nicoară, Cristian Bențe

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Optimized Time Series Feature Selection for Manufacturing AI: Reducing Complexity and Improving Classification Accuracy by Jaeseok Jang, Chanyoung Jung, Hail Jung

“…To address this, we propose two time series feature selection strategies. First, we extract meaningful variables by analyzing the time series patterns of non-defective and defective products. …”
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Surprise as a Chronotopic Feature of the World in the Poem by F.I. Tyutchev Exists in the Autumnal Growing... by Anastasia A. Aksyonova

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Enhancing DDoS Attack Classification through SDN and Machine Learning: A Feature Ranking Analysis by Aymen AlAwadi, Kawthar Rasoul ALesawi

“…Machine learning (ML) offers a promising way for early DDoS attack detection due to its ability to analyze large datasets and identify patterns. However, adding too many features to the ML might reduce its effectiveness in identifying the attacks provided by central network paradigms such as the Software-Defined Network (SDN). …”
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Features of the Technology Companies’ Development in the Context of the Introduction of Financial Technologies: Strategic Trends and OTSW-analysis by A. K. Yakovleva

“…The article reveals the content of the concept of “financial technology”, emphasizes its importance in the strategic development of technology companies in the financial sector. It reflects the features of financial technologies and services as tools to stimulate innovation in the financial sector. …”
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Features of heat and mechanical characteristics of pulsating flows in gas-air paths of piston engines with turbocharging by L. V. Plotnikov, Y. M. Brodov, B. P. Zhilkin, N. I. Grigoriev

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DFANet: A Deep Feature Attention Network for Building Change Detection in Remote Sensing Imagery by Peigeng Lu, Haiyong Ding, Xiang Tian

“…Finally, Transformer is introduced to capture long-range dependencies across bitemporal images, enabling the network to better understand feature change patterns and the relationships between different regions and land cover categories. …”
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Time-Series Representation Feature Refinement with a Learnable Masking Augmentation Framework in Contrastive Learning by Junyeop Lee, Insung Ham, Yongmin Kim, Hanseok Ko

“…Time-series data pose challenges due to their temporal dependencies and feature-extraction complexities. To address these challenges, we introduce a masking-based reconstruction approach within a contrastive learning context, aiming to enhance the model’s ability to learn discriminative temporal features. …”
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Sleep problems and sensory features in children with low-average cognitive abilities and autism spectrum disorder by Sumie Iwasaki, Yuko Yoshimura, Chiaki Hasegawa, Sanae Tanaka, Takashi Ikeda, Ken Yaoi, Tetsu Hirosawa, Mitsuru Kikuchi

“…However, it remains unclear whether sleep disturbances in children with ASD are related to intelligence or sensory features. This study examined whether sleep disturbances in children can be explained by the presence or absence of ASD characteristics, sensory features, and cognitive skills. …”
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