Travel time prediction for an intelligent transportation system based on a data-driven feature selection method considering temporal correlation by Amirreza Kandiri, Ramin Ghiasi, Maria Nogal, Rui Teixeira

“…The first stage involves an offline process where interconnected optimisation algorithms are employed to identify the optimal set of features and determine the most effective machine learning model architecture. …”
Get full text

TransC-GD-CD: Transformer-Based Conditional Generative Diffusion Change Detection Model by Yihan Wen, Zhuo Zhang, Qi Cao, Guanchong Niu

“…This approach leads to inadequate utilization of feature information, resulting in inaccurate CD maps, particularly when discerning edges. …”
Get full text

Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images by Ruhul Amin, Md.Shamim Reza, Dewan Ahmed Muhtasim, Jungpil Shin, Md. Maniruzzaman, Md.Mahfujul Hasan

“…In the proposed approach, we extracted and integrated significant features using three image feature extractors (LBP, CLBP, and HOG) with 95% PCA. …”
Get full text

Detection of Alzheimer and mild cognitive impairment patients by Poincare and Entropy methods based on electroencephalography signals by Umut Aslan, Mehmet Feyzi Akşahin

Get full text

The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…By analyzing over 100 research papers over past half-decade (2019–2024), this review fills that gap, exploring the latest methods and paradigms, summarizing key concepts, challenges, datasets, and offering insights into future directions for brain tumor detection using deep learning. This review also incorporates an analysis of previous reviews and targets three main aspects: feature extraction, segmentation, and classification. …”
Get full text

Quantitative Analysis of Sulfur Elements in Mars-like Rocks Based on Multimodal Data by Yuhang Dong, Zhengfeng Shi, Junsheng Yao, Li Zhang, Yongkang Chen, Junyan Jia

“…Furthermore, to optimize model performance, different feature selection algorithms were evaluated. Ultimately, an XGBoost-based feature selection method incorporating prior knowledge was employed to identify optimal LIBS spectral features, and the selected feature subsets were utilized in multimodal modeling to enhance stability. …”
Get full text

AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
Get full text

Resilience of Machine Learning Models in Anxiety Detection: Assessing the Impact of Gaussian Noise on Wearable Sensors by Abdulrahman Alkurdi, Jean Clore, Richard Sowers, Elizabeth T. Hsiao-Wecksler, Manuel E. Hernandez

“…The effectiveness of feature-based and end-to-end machine learning models for anxiety detection was evaluated under varying conditions of Gaussian noise. …”
Get full text

A Novel Deep Learner for Human Behavior Prediction Over Public Video Surveillance by Bayan Alabdullah, Bisma Batool Fatima, Haifa F. Alhasson, Mohammed Alshehri, Yahya AlQahtani, Nouf Albhassabi, Hui Liu

Get full text

DCS-YOLOv5s: A Lightweight Algorithm for Multi-Target Recognition of Potato Seed Potatoes Based on YOLOv5s by Zhaomei Qiu, Weili Wang, Xin Jin, Fei Wang, Zhitao He, Jiangtao Ji, Shanshan Jin

“…The DCS-YOLOv5s target detection model, by attaining model compactness, has substantially heightened the detection precision, presenting a beneficial reference for dynamic sample target detection in the context of potato-cutting machinery.…”
Get full text

Detection of the Pin Defects of Power Transmission Lines Based on Improved TPH-MobileNetv3 by Mengxuan Li, Jingshan Han, Zhi Yang, Bin Zhao, Peng Liu

“…Moreover, compared with the mainstream algorithms with the same detection accuracy, this algorithm not only reduces the model size and significantly enhances detection efficiency but also satisfies the requirement of edge image processing of power inspection.…”
Get full text

A target detection model HR-YOLO for advanced driver assistance systems in foggy conditions by Yao Zhang, Na Jia

“…Abstract To improve the accuracy and real-time performance of detection algorithms in Advanced Driver Assistance Systems (ADAS) under foggy conditions, this paper introduces HR-YOLO, an improved YOLO-based model specifically designed for vehicle and pedestrian detection. …”
Get full text

Design of Intrusion Detection and Response Mechanism for Power Grid SCADA Based on Improved LSTM and FNN by Yu Huang, Liangyuan Su

“…To improve the accuracy of such systems, the study first uses sequence feature construction algorithms to explicitly represent sequence feature information. …”
Get full text

MSUD-YOLO: A Novel Multiscale Small Object Detection Model for UAV Aerial Images by Xiaofeng Zhao, Hui Zhang, Wenwen Zhang, Junyi Ma, Chenxiao Li, Yao Ding, Zhili Zhang

“…First, the model uses an attention scale sequence fusion mode to achieve more efficient multiscale feature fusion. Meanwhile, a tiny prediction head is incorporated to make the model focus on the low-level features, thus improving its ability to detect small objects. …”
Get full text

An Infrared Small Moving Target Detection Method in Complex Scenes Based on Dual-Region Search by Huazhao Cao, Yuxin Hu, Ziming Wang, Jianwei Yang, Guangyao Zhou, Wenzhi Wang, Yuhan Liu

“…However, most existing algorithms for detecting small targets in infrared imagery encounter difficulties in achieving both high accuracy and speed, particularly in complex scenes. …”
Get full text

A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…This study presents a novel, hybrid ensemble learning-based intrusion detection framework that integrates deep learning and traditional ML algorithms with explainable artificial intelligence for real-time cybersecurity applications. …”
Get full text

A Dynamic Interference Detection Method of Underwater Scenes Based on Deep Learning and Attention Mechanism by Shuo Shang, Jianrong Cao, Yuanchang Wang, Ming Wang, Qianchuan Zhao, Yuanyuan Song, He Gao

“…This algorithm first improves the feature extraction layer of the YOLOv8 network, improves the convolutional network structure of Bottleneck, reduces the amount of calculation and improves detection accuracy. …”
Get full text

The Steel Surface Multiple Defect Detection and Size Measurement System Based on Improved YOLOv5 by Yiming Xu, Ziheng Ding, Wang Li, Kai Zhang, Le Tong

“…Finally, the steel surface defect detection and size measurement system are designed in this paper, which consist of various hardware, related measurement, and detection algorithms. …”
Get full text

Detection of kidney bean leaf spot disease based on a hybrid deep learning model by Yiwei Wang, Qianyu Wang, Yue Su, Binghan Jing, Meichen Feng

“…Based on this dataset, a novel hybrid deep learning model framework is proposed, which integrates deep learning models (EfficientNet-B7, MobileNetV3, ResNet50, and VGG16) for feature extraction with machine learning algorithms (Logistic Regression, Random Forest, AdaBoost, and Stochastic Gradient Boosting) for classification. …”
Get full text

Depression Analysis and Detection Using Machine Learning: Incorporating Gender Differences in a Comparative Study by Marina Galanina, Anna Rekiel, Anna BaCzyk, Bozena Kostek

“…Depression is a significant mental health problem and presents a challenge for the machine learning field in the detection of this illness. This study explores automated depression classification, leveraging computational techniques to address this issue. …”
Get full text