Detection of insect-damaged sunflower seeds using near-infrared hyperspectral imaging and machine learning by Bright Mensah, Jarrad Prasifka, Brent Hulke, Ewumbua Monono, Xin Sun

“…Machine learning techniques, specifically multilayer perceptron (MLP), support vector machine (SVM), random forest (RF), light gradient boosting machine (LGBM), extreme gradient boosting (XGB), gradient boosting (GB), and partial least squares discriminant analysis (PLS-DA), were trained and evaluated based on the spectral features. …”
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

Get full text

Lightweight multidimensional feature enhancement algorithm LPS-YOLO for UAV remote sensing target detection by Yong Lu, Minghao Sun

Get full text

Prostate cancer detection with transrectal in-bore MRI biopsies: impact of prostate volume and lesion features by Alexander Schaudinn, Harald Busse, Constantin Ehrengut, Nicolas Linder, Jonna Ludwig, Toni Franz, Lars-Christian Horn, Jens-Uwe Stolzenburg, Timm Denecke

“…Features were then compared for statistically significant differences in the cancer detection rate (CDR) of clinically significant (cs-PCa) and any prostate cancer (any-PCa) using categorical and continuous variables. …”
Get full text

Optimizing Feature Selection and Machine Learning Algorithms for Early Detection of Prediabetes Risk: Comparative Study by Mahmoud B Almadhoun, MA Burhanuddin

Get full text

Innovative Approach to Detecting Autism Spectrum Disorder Using Explainable Features and Smart Web Application by Mohammad Abu Tareq Rony, Fatama Tuz Johora, Nisrean Thalji, Ali Raza, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee

Get full text

TW-YOLO: An Innovative Blood Cell Detection Model Based on Multi-Scale Feature Fusion by Dingming Zhang, Yangcheng Bu, Qiaohong Chen, Shengbo Cai, Yichi Zhang

“…However, due to the diversity and complexity of blood cell images, traditional models still exhibit deficiencies in blood cell detection. To address blood cell detection, we developed the TW-YOLO approach, leveraging multi-scale feature fusion techniques. …”
Get full text

A Dual-Branch Fusion Model for Deepfake Detection Using Video Frames and Microexpression Features by Georgios Petmezas, Vazgken Vanian, Manuel Pastor Rufete, Eleana E. I. Almaloglou, Dimitris Zarpalas

“…In this paper, we propose a novel approach to deepfake detection by combining video frame analysis with facial microexpression features. …”
Get full text

A lightweight vulnerability detection method for long smart contracts based on bimodal feature fusion by Chen Yang Lin, Hui Zhao, Jing Han Liu

“…This method can combine the source code and opcode of smart contracts for analysis, and use a hierarchical attention network composed of bidirectional GRU and attention mechanism for vulnerability feature extraction. …”
Get full text

PFRNet: A Small Object Detection Method Based on Parallel Feature Extraction and Attention Mechanism by Hai Lin, Ji Wang, Jingguo Li

“…Visualization analysis reveals that the PFR module effectively captures richer and more comprehensive visual features in images, providing robust input for subsequent detection tasks, which is crucial for PFRNet’s superior performance. …”
Get full text

The Detection and Classification of Grape Leaf Diseases with an Improved Hybrid Model Based on Feature Engineering and AI by Fatih Atesoglu, Harun Bingol

“…Therefore, the early detection and classification of grape diseases with the latest artificial intelligence techniques and feature reduction techniques was carried out within the scope of this study. …”
Get full text

Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques by S. Vijayalakshmi, Binay Kumar Pandey, Digvijay Pandey, Mesfin Esayas Lelisho

“…This study presents a hybrid classification approach for mammogram analysis by combining handcrafted statistical features and deep learning techniques. …”
Get full text

Predictive Analysis of Maritime Congestion Using Dynamic Big Data and Multiscale Feature Analysis by Yalin Wu

“…This study proposes an innovative congestion prediction approach using dynamic big data analysis of vessel trajectories and multiscale feature analysis. …”
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

“…Current methods for epilepsy EEG signal recognition typically extract and represent features from multiple dimensions, such as temporal, spectral, and time–frequency analysis. …”
Get full text

BEVCorner: Enhancing Bird’s-Eye View Object Detection with Monocular Features via Depth Fusion by Jesslyn Nathania, Qiyuan Liu, Zhiheng Li, Liming Liu, Yipeng Gao

Get full text

FAMHE-Net: Multi-Scale Feature Augmentation and Mixture of Heterogeneous Experts for Oriented Object Detection by Yixin Chen, Weilai Jiang, Yaonan Wang

“…These deficiencies can lead to insufficient feature representation and reduced detection accuracy. …”
Get full text

Chronic liver disease detection using ranking and projection-based feature optimization with deep learning by Sumaiya Noor, Salman A. AlQahtani, Salman Khan

“…The approach integrates multiple ranking and projection techniques for features, utilizing deep learning to detect early signs of liver disease. …”
Get full text

Precise Crop Pest Detection Based on Co-Ordinate-Attention-Based Feature Pyramid Module by Chenrui Kang, Lin Jiao, Kang Liu, Zhigui Liu, Rujing Wang

Get full text

Early Detection of ITSC Faults in PMSMs Using Transformer Model and Transient Time-Frequency Features by Ádám Zsuga, Adrienn Dineva

“…Existing diagnostic approaches, including motor current signature analysis (MCSA) and wavelet-based methods, are primarily designed for steady-state conditions and rely on manual feature selection, limiting their applicability in real-time embedded systems. …”
Get full text

Leveraging spatial dependencies and multi-scale features for automated knee injury detection on MRI diagnosis by Jianhua Sun, Ye Cao, Ying Zhou, Baoqiao Qi

“…BackgroundThe application of deep learning techniques in medical image analysis has shown great potential in assisting clinical diagnosis. …”
Get full text