Factor Investment or Feature Selection Analysis? by Jifang Mai, Shaohua Zhang, Haiqing Zhao, Lijun Pan

“…Secondly, Deep Feedforward Neural Networks (DFN) exhibited exceptional performance in portfolio management, significantly outperforming other evaluated machine learning methods, and achieving high levels of out-of-sample performance and Sharpe ratios. …”
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Crash severity prediction using a virtual geometry-group-based deep learning approach with images-based feature representation by Nanon Sonnatthanon, Kasem Choocharukul

“…The model's performance is evaluated using two key indicators: the F1-score and the Area Under the Curve. …”
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Performance Evaluation of Various Deep Learning Models in Gait Recognition Using the CASIA-B Dataset by Nakib Aman, Md. Rabiul Islam, Md. Faysal Ahamed, Mominul Ahsan

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Classification of Brain Tumors by Using a Hybrid CNN-SVM Model by Talitha Safa Nabila, Abu Salam

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Design and Evaluation of ADANet: A High-Fidelity Motion Acquisition Framework for Assistive Gesture-Based Interfaces by Md Ettashamul Haque, Atique Tajwar, Akm Azad, Salem A. Alyami, Md Mehedi Hasan

“…To address these limitations, this article presents ADANet — Advanced Disability Assistive Neural Network-driven framework for accelerometer-based gesture recognition, tailored for wearable assistive applications. …”
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Synthesis and evaluation of seamless, large-scale, multispectral satellite images using Generative Adversarial Networks on land use and land cover and Sentinel-2 data by Torben Dedring, Andreas Rienow

“…Based on several metrics, such as difference calculations, the spectral information divergence (SID), and the Fréchet inception distance (FID), we evaluate the resulting images. The models reach mean SIDs as low as 0.026 for urban fabrics and forests and FIDs below 90 for bands B2 and B5 showing that the CGAN is capable of synthesizing distinct synthetic features matching with features typical for respective LULC categories and manages to mimic multispectral signatures. …”
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A comprehensive guide to selecting suitable wavelet decomposition level and functions in discrete wavelet transform for fault detection in distribution networks by Esraa M. Shalby, Almoataz Y. Abdelaziz, Eman S. Ahmed, Basem Abd-Elhamed Rashad

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Image Experience Prediction for Historic Districts Using a CNN-Transformer Fusion Model by Weijia Wang, Youping Teng, Lu Yan, Longwei Wu, Yinying Yang, Zijian Luo

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Cattle welfare assessment based on adaptive fuzzy logic and multimodal data fusion by Lei Tong, Lei Tong, Lei Tong, Jiandong Fang, Jiandong Fang, Jiandong Fang, Xiuling Wang, Xiuling Wang, Xiuling Wang, Yudong Zhao, Yudong Zhao

“…The method establishes a quantitative scoring system based on behavioral duration and individual group differences, and designs a multi-modal data processing framework that combines Backpropagation (BP) neural networks with adaptive fuzzy logic. This framework uses a Gaussian membership function to replace the traditional triangular membership function for feature mapping, significantly improving the robustness and accuracy of the evaluation system through a differentiated weight allocation strategy. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
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Assessment of Knot-Induced Degradation in Timber Beams: Probabilistic Modeling and Data-Driven Prediction of Load Capacity Loss by Peixuan Wang, Guoming Liu, Fanrong Li, Shengcai Li, Gabriele Milani, Donato Abruzzese

“…Finally, a predictive model based on a fully connected neural network is developed; feature analysis indicates that the longitudinal position of knots exerts a stronger nonlinear influence on load capacity than radial depth or diameter. …”
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Practical guidelines for cell segmentation models under optical aberrations in microscopy by Boyuan Peng, Jiaju Chen, P. Bilha Githinji, Ijaz Gul, Qihui Ye, Minjiang Chen, Peiwu Qin, Xingru Huang, Chenggang Yan, Dongmei Yu, Jiansong Ji, Zhenglin Chen

“…Deep learning methods, particularly convolutional neural networks (CNNs), have revolutionized cell segmentation by extracting intricate features from images. …”
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Analysis of Facial Areas to Identify CHD Risks Based on Facial Textures by Budi Sunarko, Agung Adi Firdaus, Yudha Andriano Rismawan, Anan Nugroho

“…This study aimed to develop and evaluate a machine learning model or diagnose CHD using facial texture features and to compare the performance across different facial regions to provide recommendations for improvement. …”
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A Highly Accurate Adverse Drug Reactions (ADR) Detection from Medical Forum Comments Using Long Short-Term Memory Networks by Anjali Basagodu Veeresh, Ravikumar Guralamata Krishnegowda, Shashikala Salekoppalu Venkataramu

“…Further, the features are converted into LSTM networks to perform the testing operation using the above features. …”
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Para-YOLO: An Efficient High-Parameter Low-Computation Algorithm Based on YOLO11n for Remote Sensing Object Detection by Hang Chen, Qi Cao, Yongqiang Wang, Shang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…By utilizing the intermediate layer of the feature fusion network as the aggregation-diffusion layer, it mitigates the feature degradation caused by consecutive upsampling in Feature Pyramid Networks. …”
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Lightweight Dual-Stream SAR–ATR Framework Based on an Attention Mechanism-Guided Heterogeneous Graph Network by Xuying Xiong, Xinyu Zhang, Weidong Jiang, Tianpeng Liu, Yongxiang Liu, Li Liu

“…Additionally, we include a convolutional neural network based feature extraction net to replenish intuitive visual features. …”
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Ranking Assisted Unsupervised Morphological Disambiguation of Turkish by Hayri Volkan Agun, Ozkan Aslan

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Improving Aerobics Posture Evaluation by Transfer Learning: Humanized Computational Application of BERT-PTA Domain Adaptive Methods by Wenting Zhou, Biao Guo, Feng Cao

“…Second, the BERT-PTA model was used to extract features from the preprocessed posture data. Next, a convolutional neural network was used to construct a key point localization model for aerobics poses, and transfer learning was used to train and fine-tune the model. …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

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Establishment and validation of a combined diagnostic model for aldosterone-producing adenoma of the adrenal gland based on CT radiomics and clinical features by ZHANG Mingquan, LIU Jingjing, LIN Xin, FU Min, FENG Ying, CHEN Jingjing

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