Optimizing Cervical Cancer Diagnosis with Feature Selection and Deep Learning by Łukasz Jeleń, Izabela Stankiewicz-Antosz, Maria Chosia, Michał Jeleń

“…This study investigates the effectiveness of combining handcrafted feature-based methods with convolutional neural networks for the determination of cancer histological type, emphasizing the role of feature selection in enhancing classification accuracy. …”
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Feature Graph Construction With Static Features for Malware Detection by Binghui Zou, Chunjie Cao, Longjuan Wang, Yinan Cheng, Chenxi Dang, Ying Liu, Jingzhang Sun

“…Malware can greatly compromise the integrity and trustworthiness of information and is in a constant state of evolution. Existing feature fusion-based detection methods generally overlook the correlation between features. …”
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Employing Neural Networks, Fuzzy Logic, and Weibull Analysis for the Evaluation of Recycled Brick Powder in Concrete Compositions by Mohammad Mohtasham Moein, Komeil Rahmati, Ali Mohtasham Moein, Ashkan Saradar, Sam E. Rigby, Amin Akhavan Tabassi

“…Additionally, an impact damage evolution equation was presented for mixtures containing RBP. …”
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Smart adaptive learning and optimized feature clustering for enhanced image retrieval by P. Umaeswari, Sujata Patil, Parameshachari Bidare Divakarachari, Przemysław Falkowski-Gilski

“…CBIR extracts key features related to texture, shape, and color using techniques such as Local Binary Pattern, Zernike Moments, and Color Moments. …”
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AI Painting Effect Evaluation of Artistic Improvement with Cross-Entropy and Attention by Yihuan Tian, Shiwen Lai, Zuling Cheng, Tao Yu

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MultiV_Nm: a prediction method for 2′-O-methylation sites based on multi-view features by Lei Bai, Fei Liu, Yile Wang, Junle Su, Lian Liu

“…By integrating the powerful local feature extraction ability of convolutional neural networks, the ability of graph attention networks to capture global structural information, and the efficient interaction advantage of cross-attention mechanisms for different features, it deeply explores and integrates multi-view features, and finally realizes the prediction of Nm modification sites. …”
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SSL-SurvFormer: A Self-Supervised Learning and Continuously Monotonic Transformer Network for Missing Values in Survival Analysis by Quang-Hung Le, Brijesh Patel, Donald Adjeroh, Gianfranco Doretto, Ngan Le

“…This entails a continuously <i>monotonic Transformer network</i>, empowered by <i>SSL pre-training</i>, that is designed to address the challenges presented by <i>continuous events and absent features</i> in survival prediction. …”
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Predicting Index Trend Using Hybrid Neural Networks with a Focus on Multi-Scale Temporal Feature Extraction in the Tehran Stock Exchange by Mohammad Osoolian, Ali Nikmaram, Mahdi Karimi

“…MethodsThe hybrid neural network architecture that has been put forward integrates the unique capabilities of convolutional neural networks (CNNs) in the realm of feature extraction with the effectiveness of long short-term memory (LSTM) networks in capturing temporal dependencies. …”
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The evaluation model of engineering practice teaching with complex network analytic hierarchy process based on deep learning by Xianlong Han, Xiaohui Chen

“…A brand-new teaching evaluation model is constructed based on the Internet of Things (IoT) technology, combined with complex network analytic hierarchy process and deep learning method. …”
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Evaluation of Time-Domain Acoustic Signature in TIG Welding of 5083 Aluminum Alloy: A Methodological Comparison of Feature Reduction Approaches by V M Gautham, A Sumesh, E V Jithin, K Rameshkumar, Dinu Thomas Thekkuden

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Research on the Evaluation of the Node Cities of China Railway Express Based on Machine Learning by Chenglin Ma, Mengwei Zhou, Wenchao Kang, Haolong Wang, Jiajia Feng

“…However, the systematic evaluation of CR Express node cities remains understudied, hindering the optimization of logistics networks and sustainable development goals. …”
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Comparative Analysis of Deep Learning-Based Feature Extractors for Change Detection in Automotive Radar Maps by Harihara Bharathy Swaminathan, Aron Sommer, Uri Iurgel, Andreas Becker, Martin Atzmueller

“…The Siamese network architecture has been applied by deep learning practitioners to find similarities between images. …”
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Design and Evaluation of a Framework for Cooperative and Adaptive QoS Control of DSRC Network for Road Safety Applications by Wenyang Guan, Jianhua He, Zuoyin Tang, Thomas M. Chen

“…After an analysis of the system application requirements and the DSRC vehicle network features, we propose a framework for cooperative and adaptive QoS control, which is believed to be a key for the success of DSRC on supporting effective collaborative road safety applications. …”
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Hybrid Feature-Based Disease Detection in Plant Leaf Using Convolutional Neural Network, Bayesian Optimized SVM, and Random Forest Classifier by Ashutosh Kumar Singh, SVN Sreenivasu, U.S.B. K. Mahalaxmi, Himanshu Sharma, Dinesh D. Patil, Evans Asenso

“…This paper follows two methodologies and their simulation outcomes are compared for performance evaluation. In the first part, data augmentation is performed on the PlantVillage data set images (for apple, corn, potato, tomato, and rice plants), and their deep features are extracted using convolutional neural network (CNN). …”
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Synergistic use of handcrafted and deep learning features for tomato leaf disease classification by Mohamed Bouni, Badr Hssina, Khadija Douzi, Samira Douzi

“…It utilizes enhancement filters and segmentation algorithms to isolate with Regions-of-Interests (ROI) in images tomato leaves. These features based arranged in ABCD rule (Asymmetry, Borders, Colors, and Diameter) are integrated with outputs from a Convolutional Neural Network (CNN) pretrained on ImageNet. …”
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Joint Grid-Based Attention and Multilevel Feature Fusion for Landslide Recognition by Xinran Li, Tao Chen, Gang Liu, Jie Dou, Ruiqing Niu, Antonio Plaza

“…However, CNNs cannot accurately characterize long-distance dependencies and global information, while the transformer may not be as effective as CNNs in capturing local features and spatial information. To address these limitations, we construct a new LR network based on grid-based attention and multilevel feature fusion (GAMTNet). …”
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Research on defect perception model of distribution network based on big data analysis and waveform matching algorithm by LIN Kaifeng, LI Yiming, ZHANG Bo, YANG Changyu, ZHU Zeting, YANG Zhenda

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IoT-based prediction model for aquaponic fish pond water quality using multiscale feature fusion with convolutional autoencoder and GRU networks by Suma Christal Mary Sundararajan, Yamini Bhavani Shankar, Sinthia Panneer Selvam, Nalini Manogaran, Koteeswaran Seerangan, Deepa Natesan, Shitharth Selvarajan

“…After that, these data are forwarded to the feature extraction phase. The weighted features, DBN (Deep Belief Network) features, and the original features are achieved in the feature extraction stage. …”
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Multimodal sleep staging network based on obstructive sleep apnea by Jingxin Fan, Jingxin Fan, Jingxin Fan, Mingfu Zhao, Li Huang, Li Huang, Bin Tang, Bin Tang, Lurui Wang, Zhong He, Zhong He, Xiaoling Peng

“…It adaptively fuses the weights of features to enhance the robustness of the model. Finally, multiple channel data are integrated to address the heterogeneity between different modalities effectively and alleviate the impact of OSA on sleep stages.ResultsWe evaluated MSDC-SSNet on three public datasets and our collection of PSG records of 17 OSA patients. …”
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Optimizing Fingerprint Identification: CNNs With Raw Images Versus Handcrafted Features for Real-Time Systems by Shaik Salma, Tauheed Ahmed, Garimella Ramamurthy

“…This study investigates the balance between accuracy and computational efficiency(thereby speed) by comparing two approaches: training a Convolutional Neural Network (CNN) with raw fingerprint images and training a CNN using handcrafted fingerprint features. …”
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