Automated ECG Arrhythmia Classification Using Feature Images with Common Matrix Approach-Based Classifier by Ali Kirkbas, Aydin Kizilkaya

“…The classification process is performed with feature images applied as input to the classifier model. …”
Get full text

Explainable CNN for brain tumor detection and classification through XAI based key features identification by Shagufta Iftikhar, Nadeem Anjum, Abdul Basit Siddiqui, Masood Ur Rehman, Naeem Ramzan

“…This complexity can hinder the transparency of the decision-making process, causing models to rely on irrelevant features or normal soft tissues. …”
Get full text

A Wind Power Forecasting Method Based on Lightweight Representation Learning and Multivariate Feature Mixing by Chudong Shan, Shuai Liu, Shuangjian Peng, Zhihong Huang, Yuanjun Zuo, Wenjing Zhang, Jian Xiao

“…As an effective feature extraction technique, representation learning can better capture complex feature relationships and improve forecasting performance. …”
Get full text

Multi-CNN Deep Feature Fusion and Stacking Ensemble Classifier for Breast Ultrasound Lesion Classification by Kemal PANÇ, Sümeyye SEKMEN

“…The results for the malignant class were AUC: 0.916, F1 score: 0.79. Feature importance analysis showed that ResNet50V2 had the highest contribution to the model’s performance. …”
Get full text

Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms by Maryam Askari, Farid Khoshalhan, Hodjat Hamidi

“…Feature selection is crucial in machine learning and data mining, significantly impacting model performance and efficiency by reducing dimensionality, mitigating overfitting, and improving interpretability. …”
Get full text

Exploring functional zone-dependent nonlinear associations between objective features and subjective perceptions: A case study in Beijing by Zixuan Wang, Xiang Zhang, Yuchuan Zhou, Yiyi Jiang, Haibin Xu

“…Model performance was robust, with XGBoost achieving the highest average R2 (0.221) and one of the lowest average RMSE values (0.031) compared to four baseline machine learning models, underscoring its generalizability across perception dimensions and functional zone types. …”
Get full text

Classification of multi-lead ECG based on multiple scales and hierarchical feature convolutional neural networks by Feiyan Zhou, Duanshu Fang

“…The cross-dataset experimental results also confirm the model’s strong generalization capability.…”
Get full text

A novel similarity-constrained feature selection method for epilepsy detection via EEG signals by Chunlei Shi, Jun Gao, Jian Yu, Lingzhi Zhao, Faxian Jia

“…However, excessive feature extraction can increase model complexity and reduce generalization performance. …”
Get full text

Landslide susceptibility assessment using lightweight dense residual network with emphasis on deep spatial features by Shenghua Xu, Zhuolu Wang, Jiping Liu, Xinrui Ma, Tingting Zhou, Qing Tang

“…Therefore, the proposed model can better fit the complex nonlinear relationship in landslide susceptibility, effectively mine deep spatial features, and address the high computational costs associated with complex networks.…”
Get full text

Computationally integrating radiology and pathology image features for predicting treatment benefit and outcome in lung cancer by Pranjal Vaidya, Mohammadhadi Khorrami, Kaustav Bera, Pingfu Fu, Lukas Delasos, Amit Gupta, Cristian Barrera, Nathan A. Pennell, Vamsidhar Velcheti, Anant Madabhushi

Get full text

Hybrid Optimized Feature Selection and Deep Learning Method for Emotion Recognition That Uses EEG Data by asmaa Bashar Hmaza, Rajaa K. Hasoun

“…Although the GRU and simple RNN models exhibit good performance in emotion identification, their measurements are less than those of LSTM, which outperforms all the other models. …”
Get full text

Enhanced Heart Disease Diagnosis Using Machine Learning Algorithms: A Comparison of Feature Selection by Hirmayanti, Ema Utami

“…Based on the performance of the model using the selected relevant features, it shows that the proposed CFS-SVM shows good and efficient performance in diagnosing heart disease.…”
Get full text

Optimizing Fingerprint Identification: CNNs With Raw Images Versus Handcrafted Features for Real-Time Systems by Shaik Salma, Tauheed Ahmed, Garimella Ramamurthy

“…Statistical analyses (t-tests, ANOVA, and F-statistics) confirmed the significance of these performance differences (<inline-formula> <tex-math notation="LaTeX">${p} \lt 0.01$ </tex-math></inline-formula>) and demonstrated the model&#x2019;s reliability, robustness, and consistency. …”
Get full text

Human Sitting-Posture Recognition Based on the Cascade of Feature Mapping Nodes Broad Learning System by LI Hongjun; SUN Wanting; ZHOU Ze; LI Chaobo; ZHANG Shibing

“…The experimental results in public datasets and self-built dataset show that the model not only achieves better performance on public datasets, but also has the average recognition accuracy of 99.90% on images and 79.21% on videos, which is 5.5%higher than the classic broad learning system. …”
Get full text

Mitigating Multicollinearity in Induction Motors Fault Diagnosis Through Hierarchical Clustering-Based Feature Selection by Bassam A. Hemade, Sabbah Ataya, Attia A. El-Fergany, Nader M. A. Ibrahim

“…A novel feature selection approach based on agglomerative hierarchical clustering (AHC) is proposed to mitigate feature redundancy and enhance model generalization. …”
Get full text

Emotion recognition in panoramic audio and video virtual reality based on deep learning and feature fusion by Siqi Guo, Mian Wu, Chunhui Zhang, Ling Zhong

“…The proposed algorithm was significantly superior to the comparison algorithm. A performance comparison was conducted between panoramic audio and video virtual reality emotion recognition models based on the improved algorithm. …”
Get full text

AquaYOLO: Advanced YOLO-based fish detection for optimized aquaculture pond monitoring by M. Vijayalakshmi, A. Sasithradevi

“…DePondFi dataset contains around 50k bounding box annotations across 8150 images. Proposed AquaYOLO model performs well, achieving a precision, recall and mAP@50 of 0.889, 0.848, and 0.909 respectively. …”
Get full text

Interpersonal Relationship Detection Using Multi-Head Graph Attention Networks With Multi-Feature Fusion by Simge Akay, Duygu Cakir, Nafiz Arica

“…The model&#x2019;s performance is evaluated on two benchmark datasets: the Interpersonal Relation Dataset (IPR) and People in Social Context (PISC). …”
Get full text

Teaching Machines on Snoring: A Benchmark on Computer Audition for Snore Sound Excitation Localisation by Kun QIAN, Christoph JANOTT, Zixing ZHANG, Jun DENG, Alice BAIRD, Clemens HEISER, Winfried HOHENHORST, Michael HERZOG, Werner HEMMERT, Björn SCHULLER

“…In addition, we explore the performance of each kind of feature when it is fed into varied classifier models, including support vector machines, $k$-nearest neighbours, linear discriminant analysis, random forests, extreme learning machines, kernel-based extreme learning machines, multilayer perceptrons, and deep neural networks. …”
Get full text

Improving kidney segmentation in pathological images: a multiscale approach to resolve fragmentation and incomplete boundaries by Muhammad Wajeeh Us Sima, Chengliang Wang, Muhammad Arshad, Jamshed Ali Shaikh, Reem Ibrahim Alkanhel, Dina S. M. Hassan, Ammar Muthanna

“…We evaluated InFeNet on two datasets, where it outperformed state-of-the-art models, demonstrating superior accuracy and predictive performance. …”
Get full text