Mamba-UAV-SegNet: A Multi-Scale Adaptive Feature Fusion Network for Real-Time Semantic Segmentation of UAV Aerial Imagery by Longyang Huang, Jintao Tan, Zhonghui Chen

“…However, challenges such as class imbalance, small-object detection, and intricate boundary details complicate the analysis of UAV imagery. …”
Get full text

Comprehensive framework for thyroid disorder diagnosis: Integrating advanced feature selection, genetic algorithms, and machine learning for enhanced accuracy and other performance... by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Anchal Sharma, Surita Maini, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid, Rohit Bansal

“…The data pre-processed included handling missing values, feature scaling, and correlation analysis. In this case, the performance metrics used for model evaluation are accuracy, F1 Score, sensitivity, specificity, precision, and Cohen's Kappa with 80% of the dataset to train the model and the rest 20% used to test it. …”
Get full text

Validation of a Novel Endoscopic Feature that Predicts Helicobacter pylori-negative Status: Does the Scratch Sign Reflect H. pylori Non-infection? by Jun-young Seo, Hyo-Jin Cho, Sang Jong Park, Ah Young Lee, Sang-Jung Kim, Ji Yong Ahn

“…In addition to the Kyoto classification of gastritis, detection of the scratch sign may facilitate identification of the H. pylori infection status.…”
Get full text

Enhancing knee osteoarthritis detection with AI, image denoising, and optimized classification methods and the importance of physical therapy methods by Burak Bugday, Harun Bingol, Muhammed Yildirim, Bilal Alatas

“…In this way, it is aimed to bring together different features of the same image. Then, feature selection was made using the neighborhood component analysis (NCA) method for the developed system to produce more successful results, and the optimized feature map was classified into six different classifiers. …”
Get full text

Apple Detection via Near-Field MIMO-SAR Imaging: A Multi-Scale and Context-Aware Approach by Yuanping Shi, Yanheng Ma, Liang Geng

“…Addressing challenges such as weak scattering, low texture contrast, and complex backgrounds in SAR images, we propose an innovative detection framework integrating Dynamic Spatial Pyramid Pooling (DSPP), Recursive Feature Fusion Network (RFN), and Context-Aware Feature Enhancement (CAFE) modules. …”
Get full text

Detection method on pantograph-catenary arcing of electric locomotives based on multi-frequency-band characteristics of current signals by LUO Yinbei, GE Ting, SUN Zeyong

“…Most existing detection methods rely on optical instruments to capture pantograph-catenary images, followed by the analysis of these images to identify arc spectra as evidence of arcing occurrences. …”
Get full text

CGD-CD: A Contrastive Learning-Guided Graph Diffusion Model for Change Detection in Remote Sensing Images by Yang Shang, Zicheng Lei, Keming Chen, Qianqian Li, Xinyu Zhao

“…Ultimately, high-quality difference images are generated from the extracted bi-temporal features, then use thresholding analysis to obtain a final change map. …”
Get full text

A Machine-Learning-Based Approach for the Detection and Mitigation of Distributed Denial-of-Service Attacks in Internet of Things Environments by Sebastián Berríos, Sebastián Garcia, Pamela Hermosilla, Héctor Allende-Cid

“…This research highlights the importance of efficient data preprocessing and feature selection for improving detection capabilities in IoT/Cloud infrastructures. …”
Get full text

Fault Detection and Identification for Nonlinear Process Based on Inertia-Based KEPCA and a New Combined Monitoring Index by Loubna El Fattahi, El Hassan Sbai

“…In the present study, we introduce a new approach for the nonlinear monitoring process based on kernel entropy principal component analysis (KEPCA) and the notion of inertia. KEPCA plays double roles. …”
Get full text

Function of 18F-FDG PET/CT radiomics in the detection of checkpoint inhibitor-induced liver injury (CHILI) by Clémence M. C. Huigen, Alexander Coukos, Sofiya Latifyan, Marie Nicod Lalonde, Niklaus Schaefer, Daniel Abler, Adrien Depeursinge, John O. Prior, Montserrat Fraga, Mario Jreige

“…The patients’ liver and spleen were contoured on the anonymized PET/CT imaging data, followed by radiomics feature extraction. Principal component analysis (PCA) and Bonferroni corrections were used for statistical analysis and exploration of radiomics features related to CHILI. …”
Get full text

An intelligent method for detection of small target fungal wheat spores based on an improved YOLOv5 with microscopic images by Zhizhou Ren, Kun Liang, Yingqi Zhang, Jinpeng Song, Xiaoxiao Wu, Chi Zhang, Xiuming Mei, Yi Zhang, Xin Liu

Get full text

Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches by Nafiseh Hosseini, Hamid Tanzadehpanah, Amin Mansoori, Mostafa Sabzekar, Gordon A. Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

Get full text

An explainable AI-driven transformer model for spoofing attack detection in Internet of Medical Things (IoMT) networks by Mohammad A. Alsharaiah, Mohammed Amin Almaiah, Rami Shehab, Mansour Obeidat, Fuad Ali El-Qirem, Theyazn Aldhyani

“…To enhance model interpretability and foster trust in AI-driven security systems, we integrate Explainable AI (XAI) techniques, specifically SHAP analysis, allowing for a deeper understanding of feature contributions in decision-making. …”
Get full text

Code-mixing unveiled: Enhancing the hate speech detection in Arabic dialect tweets using machine learning models. by Ali Alhazmi, Rohana Mahmud, Norisma Idris, Mohamed Elhag Mohamed Abo, Christopher Ifeanyi Eke

“…Recognizing this research vacuum, the study aims to close it by examining how well machine learning models containing variation features can detect hate speech, especially when it comes to Arabic tweets featuring code-mixing. …”
Get full text

Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedback by Li Ping, Ning Tao

“…Additionally, students showed higher levels of fluency, with most achieving a level of 4 or above, whereas traditional methods resulted in lower fluency levels. Spectral feature analysis indicated that the amplitude of speech signals obtained using the proposed method closely matched the original signals, unlike the discrepancies found in previous methods.DiscussionThese findings highlight the effectiveness of the proposed method, showcasing its ability to improve pronunciation accuracy and fluency. …”
Get full text

YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking by Youyu Zhou, Shu Dong, Hao Sheng, Wei Ke

“…Furthermore, a Parallel Spatial Attention (PSA) mechanism is incorporated to enhance multi-target feature discrimination. These enhancements enable the model to achieve a high detection accuracy of 98.6% mAP@0.5 while maintaining low computational complexity (2.35 M parameters, 3.11 GFLOPs). …”
Get full text

A Complementary Dataset of Scalp EEG Recordings Featuring Participants with Alzheimer’s Disease, Frontotemporal Dementia, and Healthy Controls, Obtained from Photostimulation EEG by Aimilia Ntetska, Andreas Miltiadous, Markos G. Tsipouras, Katerina D. Tzimourta, Theodora Afrantou, Panagiotis Ioannidis, Dimitrios G. Tsalikakis, Konstantinos Sakkas, Emmanouil D. Oikonomou, Nikolaos Grigoriadis, Pantelis Angelidis, Nikolaos Giannakeas, Alexandros T. Tzallas

Get full text

A hybrid deep learning model EfficientNet with GRU for breast cancer detection from histopathology images by M. Pradeepa, B. Sharmila, M. Nirmala

“…Abstract Breast cancer remains a significant global health challenge among women, with histopathological image analysis playing a critical role in early detection. …”
Get full text

A Unified Deep Learning Ensemble Framework for Voice-Based Parkinson’s Disease Detection and Motor Severity Prediction by Madjda Khedimi, Tao Zhang, Chaima Dehmani, Xin Zhao, Yanzhang Geng

“…This study presents a hybrid ensemble learning framework for the joint detection and motor severity prediction of Parkinson’s disease (PD) using biomedical voice features. …”
Get full text

A review of deep-learning-based models for afaan oromo fake news detection on social media networks by Kedir Lemma Arega, Kula Kekeba Tune, Asrat Mulatu Beyene, Wegderes Tariku, Nurhussen Menza Bune

“…Key components include a literature review, dataset compilation, preprocessing, feature extraction, model selection, training and validation, evaluation metrics, results analysis, discussion, and future work recommendations. …”
Get full text