Multi-Step Natural Gas Load Forecasting Incorporating Data Complexity Analysis with Finite Features by Ning Tian, Bilin Shao, Huibin Zeng, Meng Ren, Wei Zhao, Xue Zhao, Shuqiang Wu

“…The results indicate that compared to other models, the proposed method (XGBoost-VMD-GRU considering complex features) demonstrates superior performance in forecasting, with R² of 0.9922, 0.9860, and 0.9679 for one-step, three-step, and six-step prediction, respectively. …”
Get full text

MEFA-Net: Multilevel Feature Extraction and Fusion Attention Network for Infrared Small-Target Detection by Jingcui Ma, Nian Pan, Dengyu Yin, Di Wang, Jin Zhou

“…The experimental results confirm that the proposed algorithm model surpasses most existing recent methods. Compared with the baseline, the intersection over union (IoU) and probability of detection <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mi>d</mi></mrow></msub></mrow></semantics></math></inline-formula> of MEFA-Net on the IRSTD-1k dataset are increased by 2.25% and 3.05%, respectively, achieving better detection performance and a lower false alarm rate in complex scenarios.…”
Get full text

Enhancing parkinson disease detection through feature based deep learning with autoencoders and neural networks by P. Valarmathi, Y. Suganya, K. R. Saranya, S. Shanmuga Priya

“…Upon analyzing the accuracy, it became apparent that the Feature-Based Deep Neural Network (FB-DNN) exhibited superior performance compared to the other models. …”
Get full text

A Self-Supervised Monocular Depth Estimation Framework Based on Detail Recovery and Feature Fusion by Shun Li, Chongzheng Huang, Xiangzhe Li, Zhengyou Liang

“…Specifically, ASAM selectively emphasizes critical features and spatial locations in images to enhance the model&#x2019;s ability to capture details. …”
Get full text

Advancing the accuracy of tyrosinase inhibitory peptides prediction via a multiview feature fusion strategy by Watshara Shoombuatong, Nalini Schaduangrat, Nutta Homdee, Saeed Ahmed, Pramote Chumnanpuen

“…Finally, to maximize the utility of each feature, we fused probability-based and sequence-based features, generating more informative feature that were used to develop the final prediction model. …”
Get full text

Zero-Shot Detection of Visual Food Safety Hazards via Knowledge-Enhanced Feature Synthesis by Lanting Guo, Xiaoyu Hu, Wenhe Liu, Yang Liu

“…Using this graph as the prior knowledge, our system synthesizes discriminative visual features for unseen hazard classes through a multi-source graph fusion module and region feature diffusion model. …”
Get full text

Cooperation Spectrum Sensing Detecting Algorithm Based on Featured Belief Points in Cognitive Radio Network by Hongyan Zheng, Bo Wu, Yanpeng Feng, Xianjun Meng

“…In order to solve the dilemma of the tradeoff between spectrum sensing performance and spectrum sensing efficiency in cognitive radio network，a nove1 ED/FD cooperation spectrum sensing algorithm based on featured belief points was proposed. …”
Get full text

Robust Hybrid Data-Level Approach for Handling Skewed Fat-Tailed Distributed Datasets and Diverse Features in Financial Credit Risk by Musara Keith R, Ranganai Edmore, Chimedza Charles, Matarise Florence, Munyira Sheunesu

“…The results suggested that our novelty, SMOTEENN-ENC, integrated with the XGBoost algorithm demonstrated superiority and stability in the predictive performance when applied to skewed fat-tailed distributed datasets with inherent diverse features.…”
Get full text

Integrated analysis of molecular and clinical features associated with overall survival in melanoma patients with brain metastasis by Swaminathan Kumar, Meredith S. Pelster, Merve Hasanov, Renato A. Guerrieri, Courtney W. Hudgens, Debora A. Ledesma, Fuchenchu Wang, Grant M. Fischer, Julie M. Simon, Lauren E. Haydu, Kalman V. Katlowitz, Y. N. Vashisht Gopal, Jennifer L. McQuade, Lawrence N. Kwong, Jason T. Huse, Alexander J. Lazar, Michael T. Tetzlaff, Jeffrey E. Gershenwald, Aron Y. Joon, Ken Chen, Ziyi Li, Prahlad T. Ram, Sherise D. Ferguson, Michael A. Davies

“…Multivariate analyses (MVA) were performed with significant clinical factors and all immune features without any redundant highly correlated variables in the model. …”
Get full text

InceptionDTA: Predicting drug-target binding affinity with biological context features and inception networks by Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi

“…Traditional machine learning relies on manually engineered features from limited data, leading to suboptimal performance. …”
Get full text

Ensemble Network Graph-Based Classification for Botnet Detection Using Adaptive Weighting and Feature Extraction by Muhammad Aidiel Rachman Putra, Tohari Ahmad, Dandy Pramana Hostiadi, Royyana Muslim Ijtihadie

“…The proposed model can function as an effective tool for the forensic analysis of botnet attacks, allowing network administrators to analyze the characteristics of botnet activities and anticipate potential future threats.…”
Get full text

Parkinson disease detection based on in-air dynamics feature extraction and selection using machine learning by Jungpil Shin, Abu Saleh Musa Miah, Koki Hirooka, Md. Al Mehedi Hasan, Md. Maniruzzaman

“…Finally, we employed an ML-based approach based on ensemble voting across top-performing tasks, achieving an impressive 96.99% accuracy on task-wise classification and 99.98% accuracy on task ensembles, surpassing the existing state-of-the-art model by 2% for the PaHaW dataset. …”
Get full text

Enhancing anemia detection through multimodal data fusion: a non-invasive approach using EHRs and conjunctiva images by Muhammad Ramzan, Muhammad Usman Saeed, Ghulam Ali

“…First, EHR records are preporcessed by selecting the most appropriate features using Random Forest. The features from the conjunctiva images are extracted using RCBAM (Reverse Convolution Block Attention Mechanism). …”
Get full text

VSS-SpatioNet: a multi-scale feature fusion network for multimodal image integrations by Zeyu Xiang

“…The framework employs an asymmetric encoder-decoder with a multi-scale autoencoder and a novel VSS-Spatial (VS) fusion block for local-global feature integration. Evaluations on TNO, Harvard Medical, and RoadScene datasets demonstrate superior performance. …”
Get full text

Multi-Feature Driver Variable Fusion Downscaling TROPOMI Solar-Induced Chlorophyll Fluorescence Approach by Jinrui Fan, Xiaoping Lu, Guosheng Cai, Zhengfang Lou, Jing Wen

Get full text

A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning by Mostafa Zakeri, Amirhossein Atef, Mohammad Aziznia, Azadeh Jafari

“…Our models demonstrated exceptional performance in predicting cerebral aneurysm rupture, with accuracy ranging from 0.76 to 0.82 and precision score from 0.79 to 0.83 for the test dataset. …”
Get full text

MFENet: A Multi-Feature Extraction Network for Enhanced Emotion Detection Using EEG and STFT by N. Ramesh Babu, Viswanathan Vadivel

“…Developing computationally efficient models for EEG-based emotion recognition is essential for enabling scalable and responsive brain-computer interface (BCI) systems. …”
Get full text

Spatial distribution and health risk assessment of fluoride in groundwater in the oasis of the Hotan river basin in Xinjiang, China by Ling Li, Long Ma, Zhilin Pan, Juan Xu, Fei Chen, Changde Yang, Yidan Yin

Get full text

Network level spatial temporal traffic forecasting with Hierarchical-Attention-LSTM by Tianya Zhang

Get full text

Novel feature extraction method for signal analysis based on independent component analysis and wavelet transform. by Mariusz Topolski, Jędrzej Kozal

“…Feature extraction is an important part of data processing that provides a basis for more complicated tasks such as classification or clustering. …”
Get full text