An Efficient Network-Based QoE Assessment Framework for Multimedia Networks Using a Machine Learning Approach by Parsa Hassani Shariat Panahi, Amir Hossein Jalilvand, Abolfazl Diyanat

“…QoE, a key metric for multimedia services, reflects user satisfaction with service quality. However, measuring QoE is challenging due to its subjective nature and the complexities associated with real-time feedback.This paper presents an open-source framework for assessing QoE in multimedia networks using only key network parameters. …”
Get full text

Detection Method for Safety Helmet Wearing on Construction Sites Based on UAV Images and YOLOv8 by Xin Jiao, Cheng Li, Xin Zhang, Jian Fan, Zhenwei Cai, Zhenglong Zhou, Ying Wang

“…With the increasing demand for safety management on construction sites, traditional manual inspection methods for detecting helmet usage face challenges such as low efficiency, limited coverage, and strong subjectivity, making them inadequate for modern construction site safety requirements. …”
Get full text

High resolution remote sensing image object detection algorithm based on improved YOLOv8 by ZHANG Xia, QIAO Huanyu, CAO Feng

“…In view of problems such as objects are interfered by complex background, objects are small and densely distributed, objects are multi-scale and their directions are random in high resolution remote sensing image data, an object detection algorithm for high resolution remote sensing image based on improved YOLOv8 was proposed. …”
Get full text

YOLOv8n-SSDW: A Lightweight and Accurate Model for Barnyard Grass Detection in Fields by Yan Sun, Hanrui Guo, Xiaoan Chen, Mengqi Li, Bing Fang, Yingli Cao

“…Moreover, the morphological similarity, overlapping, and occlusion between barnyard grass and rice pose challenges for reliable detection in complex environments. To address these issues, this study constructed a barnyard grass detection dataset using high-resolution images captured by a drone equipped with a high-definition camera in rice experimental fields in Haicheng City, Liaoning Province. …”
Get full text

Liveness Detection in Computer Vision: Transformer-Based Self-Supervised Learning for Face Anti-Spoofing by Arman Keresh, Pakizar Shamoi

“…We compared the performance of the proposed fine-tuned ViT model using the DINO framework against traditional models, including CNN Model EfficientNet b2, EfficientNet b2 (Noisy Student), and Mobile ViT on the face anti-spoofing task. …”
Get full text

Oak-YOLO: A high-performance detection model for automated Oak seed defect identification. by Hao Li, Zhuqi Li, Dongkui Chen, Wangyu Wu, Xuanlong He, Hongbo Mu

“…To address this challenge, we developed a high-resolution imaging system and proposed an improved YOLO-based model named Oak-YOLO for efficient and accurate defect detection in oak seeds. …”
Get full text

Feature Multi-Scale Enhancement and Adaptive Dynamic Fusion Network for Infrared Small Target Detection by Zenghui Xiong, Zhiqiang Sheng, Yao Mao

“…This study aims to address a series of challenges in infrared small target detection, particularly in complex backgrounds and high-noise environments. …”
Get full text

A Multimodal Parallel Transformer Framework for Apple Disease Detection and Severity Classification with Lightweight Optimization by Chuhuang Zhou, Xinjin Ge, Yihe Chang, Mingfei Wang, Zhongtian Shi, Mengxue Ji, Tianxing Wu, Chunli Lv

“…To address the impact of complex disease characteristics and diverse environmental factors on detection accuracy, this study proposes a multimodal parallel transformer-based approach for apple disease detection and classification. …”
Get full text

Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography by Solomon Temidayo Owolabi, Johanes A. Belle

“…Results indicate a mean soil erodibility of 0.062 ton•yr•MJ−1•mm−1, with a high bifurcation ratio (12.72) reflecting significant drainage complexity. Average form factor (0.44), elongation ratio (0.74), and wandering ratio (3.60) suggest moderate runoff and efficient drainage. …”
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 results highlight the effectiveness of FAMEH-Net in object detection within complex remote sensing images.…”
Get full text

Grounding DINO and distillation-enhanced model for advanced traffic sign detection and classification in autonomous vehicles by Hoang Ngoc Tran, Nam Nhat Ngo Nguyen, Nhi Quynh Phan Le, Thu Anh Ngoc Le, Anh Duy Nguyen

“…The self-distilled network further reduces model size by tenfold compared to baseline models (e.g., MobileNetV2, VGG16, ResNet18), yet maintains competitive accuracy, providing a robust, resource-efficient solution for real-time deployment. Our results indicate that integrating semantic grounding with distillation-based compression not only enhances traffic sign detection performance but also delivers a scalable and efficient approach for complex traffic environments. …”
Get full text

PercepWeldNet: A Novel Perception-Guided Deep Model for Welding Defect Detection by Xingxing Zhang

“…In this study, we introduce PercepWeldNet, a deep architecture designed for visual perception in welding defect detection, addressing the challenge of identifying semantically significant features within complex welding scenes. …”
Get full text

Marine object detection in forward-looking sonar images via semantic-spatial feature enhancement by Zhen Wang, Zhen Wang, Jianxin Guo, Shanwen Zhang, Nan Xu

“…However, the challenges posed by seabed reverberation noise, complex marine environments, and varying object scales significantly hinder accurate detection of diverse object categories. …”
Get full text

Wheat Leaf Disease Detection: A Lightweight Approach with Shallow CNN Based Feature Refinement by Oumayma Jouini, Mohamed Ould-Elhassen Aoueileyine, Kaouthar Sethom, Anis Yazidi

“…Improving agricultural productivity is essential due to rapid population growth, making early detection of crop diseases crucial. Although deep learning shows promise in smart agriculture, practical applications for identifying wheat diseases in complex backgrounds are limited. …”
Get full text

YOLO-UIR: A Lightweight and Accurate Infrared Object Detection Network Using UAV Platforms by Chao Wang, Rongdi Wang, Ziwei Wu, Zetao Bian, Tao Huang

“…Within the field of remote sensing, Unmanned Aerial Vehicle (UAV) infrared object detection plays a pivotal role, especially in complex environments. …”
Get full text

WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification by Taminul Islam, Toqi Tahamid Sarker, Khaled R. Ahmed, Cristiana Bernardi Rankrape, Karla Gage

“…Our research evaluates several state-of-the-art object detection architectures, including DINO Transformer (with ResNet-101 and Swin backbones), Detection Transformer (DETR), EfficientNet B4, YOLO v8, and RetinaNet. …”
Get full text

Dual Improvements DCNv4 and AsDDet Mechanisms for Small Object Detection in Aerial Imagery by Fan Jiang, Hua-Ching Chen, Song-Lin Wei, Hsuan-Ming Feng

“…This study introduces a dual enhancement mechanism integrating Deformable Convolution v4 (DCNv4) and an Asymmetric Decoupled Detection Head (AsDDet) to significantly improve the detection performance of small objects in high-altitude unmanned aerial vehicle (UAV) imagery using YOLOv11 model architecture. …”
Get full text

Low-Complexity Vibration-Based Condition Monitoring for Rolling Bearings: A Novel Instantaneous Amplitude–Frequency Approach by Sulaiman Aburakhia, Ismail Hamieh, Sami Muhaidat, Abdallah Shami

“…Additionally, its moderate computational complexity makes the method well suited for real-time monitoring using smart transducers.…”
Get full text

Detection of Q235 Mild Steel Resistance Spot Welding Defects Based on EMD-SVM by Yuxin Wu, Xiangdong Gao, Dongfang Zhang, Perry Gao

“…Real-time detection of welding defects in resistance spot welding is a complex challenge. …”
Get full text

MRC-DETR: A High-Precision Detection Model for Electrical Equipment Protection in Power Operations by Shenwang Li, Yuyang Zhou, Minjie Wang, Li Liu, Thomas Wu

“…This paper introduces MRC-DETR (Multi-Scale Re-calibration Detection Transformer), a novel framework for detecting Power Engineering Personal Protective Equipment (PEPPE) in complex electrical operating environments. …”
Get full text