Combined Application of Deep Learning and Radiomic Features for Classification of Lung CT Images by Shariati Faridoddin, V. A. Pavlov

“…The use of a convolutional neural network enabled large volumes of data to be processed, surpassing the performance of conventional methods. The analysis involved identification of significant radiomic features, such as texture, shape, and tumor boundaries, which were automatically extracted and used to train the model. …”
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Hybrid Method for Oil Price Prediction Based on Feature Selection and XGBOOST-LSTM by Shucheng Lin, Yue Wang, Haocheng Wei, Xiaoyi Wang, Zhong Wang

“…Second, using the Adaptive Copula-based Feature Selection (ACBFS), rooted in Copula theory, facilitates the integration of the influencing factors; ACBFS enhances both accuracy and stability in feature selection, thereby amplifying predictive performance and interpretability. …”
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Gait-based human recognition using partial wavelet coherence and phase features by Sagar Arun More, Pramod Jagan Deore

“…This method directly extracts the dynamic information without using any model. We got 73.26% average recognition accuracy when considered only PWC feature. …”
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UFM: Unified feature matching pre-training with multi-modal image assistants. by Yide Di, Yun Liao, Hao Zhou, Kaijun Zhu, Qing Duan, Junhui Liu, Mingyu Lu

“…In this paper, we introduce a Unified Feature Matching pre-trained model (UFM) designed to address feature matching challenges across a wide spectrum of modal images. …”
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LAF: Enhancing person re-identification via Latent-Assisted Feature Fusion by Minglang Li, Zhiyong Tao, Sen Lin, Kaihao Feng

“…Lock-Drop selectively erases prominent regions based on primary features, encouraging the model to learn from less obvious areas. …”
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A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification by Mohanad Azeez Joodi, Muna Hadi Saleh, Dheyaa Jasim Kadhim

“…The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. …”
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A Reparameterization Feature Redundancy Extract Network for Unmanned Aerial Vehicles Detection by Shijie Zhang, Xu Yang, Chao Geng, Xinyang Li

“…This mechanism processes the downsampled feature maps, enabling the model to better focus on key regions. …”
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Discovering New Prognostic Features for the Harmonic Reducer in Remaining Useful Life Prediction by Jin Wu, Lulu Jiang, Jinfu Li, Yaqiao Zhu, Jia Wang

“…In addition, in view of the local optimum and slow speed caused by the random initialization of the network model, an improved life prediction method is proposed to optimize BP neural network to improve the prediction performance. …”
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Dynamic feature selection for silicon content prediction in blast furnace using BOSVRRFE by Junyi Duan

“…Experiments with data from a large steel enterprise validate BOSVRRFE’s performance in silicon content prediction. Results show that BOSVRRFE outperforms traditional static methods in prediction accuracy, real-time adaptability, and model stability. …”
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Unsupervised Visual-to-Geometric Feature Reconstruction for Vision-Based Industrial Anomaly Detection by Dinh-Cuong Hoang, Phan Xuan Tan, Anh-Nhat Nguyen, Duc-Thanh Tran, Van-Hiep Duong, Anh-Truong Mai, Duc-Long Pham, Khanh-Toan Phan, Minh-Quang Do, Ta Huu Anh Duong, Tuan-Minh Huynh, Son-Anh Bui, Duc-Manh Nguyen, Viet-Anh Trinh, Khanh-Duong Tran, Thu-Uyen Nguyen

“…Existing multimodal methods often combine features from different modalities, leading to feature interference and degraded performance. …”
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A study of connectivity features analysis in brain function network for dementia recognition by Siying Li, Peng Wang, Zhenfeng Li, Lidong Du, Xianxiang Chen, Jie Sun, Libin Jiang, Gang Cheng, Zhen Fang

“…We also find that the edge-level features give the best performance when machine learning models are used to recognize dementia. …”
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A Hybrid Deep Learning Paradigm for Robust Feature Extraction and Classification for Cataracts by Akshay Bhuvaneswari Ramakrishnan, Mukunth Madavan, R. Manikandan, Amir H. Gandomi

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Grading Related Feature Extraction of Chinese Mitten Crab Based on Machine Vision by Sun Dawei, Li Jiangtao, Li Zhuo, Zhou Chengquan, Lu Yingfeng, Ye Hongbao

“…The performance of the constructed models in recognizing genders and predicting carapace length and width was evaluated. …”
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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

“…To tackle these challenges, this article introduces WinMRSI, a window attention-based multimodal remote sensing image matching method designed to enhance cross-modal feature extraction and information interaction. For feature extraction, a siamese network with discrete cosine transform is employed to model inter-channel dependencies and extract multiscale features from cross-modal images. …”
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Unlocking latent features of users and items: empowering multi-modal recommendation systems by Subham Raj, Sriparna Saha

“…Existing research predominantly centers on integrating multimodal features as auxiliary information within user–item interaction models. …”
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Blind HDR image quality assessment based on aggregating perception and inference features by Donghui Wan, Xiuhua Jiang, Qiangguo Yu

“…Our approach begins with multi-scale Retinex decomposition to generate reflectance maps with varying sensitivity, followed by the calculation of gradient similarities from these maps to model the perception process. Deep feature maps are then extracted from the last pooling layer of a pretrained VGG16 network to capture inference characteristics. …”
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Leaf disease detection and classification in food crops with efficient feature dimensionality reduction. by Khasim Syed, Shaik Salma Asiya Begum, Anitha Rani Palakayala, G V Vidya Lakshmi, Sateesh Gorikapudi

“…The proposed Efficient Labelled Feature Dimensionality Reduction utilizing CNN-BiLSTM (ELFDR-LDC-CNN-BiLSTM) model is compared to current models to show its effectiveness in reducing extracted features for leaf detection and classification tasks.…”
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An Agglomerative Clustering Combined with an Unsupervised Feature Selection Approach for Structural Health Monitoring by Tales Boratto, Heder Soares Bernardino, Alex Borges Vieira, Tiago Silveira Gontijo, Matteo Bodini, Dmitriy A. Martyushev, Camila Martins Saporetti, Alexandre Cury, Flávio Barbosa, Leonardo Goliatt

“…The proposed feature selection not only reduces data dimensionality but also enhances model interpretability, improving the clustering performance in terms of homogeneity, completeness, V-measure, and adjusted Rand score. …”
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Reweighting and analysing event generator systematics by neural networks on high-level features by Amon Furuichi, Sung Hak Lim, Mihoko M. Nojiri

“…Abstract The state-of-the-art deep learning (DL) models for jet classification use jet constituent information directly, improving performance tremendously. …”
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Detecting Lameness in Dairy Cows Based on Gait Feature Mapping and Attention Mechanisms by Xi Kang, Junjie Liang, Qian Li, Gang Liu

“…The proposed system comprises (1) a Cow Lameness Feature Map (CLFM) model extracting holistic gait kinematics (hoof trajectories and dorsal contour) from walking sequences, and (2) a DenseNet-Integrated Convolutional Attention Module (DCAM) that mitigates inter-individual variability through multi-feature fusion. …”
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