Insights into the Silver Camphorimine Complexes Interactions with DNA Based on Cyclic Voltammetry and Docking Studies by Joana P. Costa, Gonçalo C. Justino, Fernanda Marques, M. Fernanda N. N. Carvalho

“…The formation of a light grey product adherent to the Pt electrode in the case of {Ag(OH)} and {Ag₂(µ-O)} complexes further corroborates the interaction of the complexes with CT-DNA detected by CV. …”
Get full text

Assessing data and sample complexity in unmanned aerial vehicle imagery for agricultural pattern classification by Linara Arslanova, Sören Hese, Marcel Fölsch, Friedemann Scheibler, Christiane Schmullius

“…The study also proposes a customized set of input layers for each crop type and identifies minimum patch sizes to enhance the efficiency of detecting specific agricultural patterns. …”
Get full text

An Electrochemical Sensor for the Simultaneous Detection of Pb²⁺ and Cd²⁺ in Contaminated Seawater Based on Intelligent Mobile Detection Devices by Zizi Zhao, Wei Qu, Chengjun Qiu, Yuan Zhuang, Kaixuan Chen, Yi Qu, Huili Hao, Wenhao Wang, Haozheng Liu, Jiahua Su

“…In this study, we present an electrochemical sensor based on intelligent mobile detection devices. By combining G-COOH-MWCNTs/ZnO with differential pulse voltammetry, the sensor enables the efficient, simultaneous detection of Pb²⁺ and Cd²⁺ in seawater. …”
Get full text

Improving Object Detection in High-Altitude Infrared Thermal Images Using Magnitude-Based Pruning and Non-Maximum Suppression by Yajnaseni Dash, Vinayak Gupta, Ajith Abraham, Swati Chandna

“…We converted dataset annotations from the COCO and PASCAL VOC formats to YOLO’s required format, enabling efficient model training and inference. The results demonstrate the proposed architecture’s superior speed and accuracy, effectively handling thermal signatures and object detection. …”
Get full text

Plant Disease Detection Using an Innovative Swin-Axial Transformer by Ao Zhang, Wei Liu

“…Plant diseases are a significant threat to global agricultural production, and accurate and efficient disease detection is crucial for ensuring food security. …”
Get full text

An improved EAE-DETR model for defect detection of server motherboard by Jian Chi, Mingke Zhang, Puhon Zhang, Guowang Niu, Zhihao Zheng

“…On the PKU-Market-PCB dataset, the mAP50 reached 96.1%, and the mAP50:95 reached 65.1%.This model effectively facilitates high-precision and high-efficiency defect detection for server motherboards in complex industrial environments, thereby offering a robust solution for the intelligent manufacturing sector.…”
Get full text

Malicious Traffic Detection on Tofino Using Graph Attention Model by Xichang Gao, Lizhuang Tan, Shengpeng Chen, Peiying Zhang, Jian Wang

“…With the surge of malicious traffic in networks, existing detection methods struggle to balance real-time performance and efficiency. …”
Get full text

Enhancing Mirror and Glass Detection in Multimodal Images Based on Mathematical and Physical Methods by Jiyuan Qiu, Chen Jiang

“…Due to their reflective and transparent nature, these surfaces are often difficult to distinguish from their surrounding environments, posing substantial challenges even for advanced deep learning models tasked with performing such detection. Current research primarily relies on complex network models that learn and fuse different modalities of images, such as RGB, depth, and thermal, to achieve mirror and glass detection. …”
Get full text

An advanced three stage lightweight model for underwater human detection by Zichen Liao, Kai Hu, Yuancheng Meng, Shuai Shen

“…Abstract This study presents StarEye, a lightweight deep learning model designed for underwater human body detection (UHBD) that addresses the challenges of complex underwater environments. …”
Get full text

Underwater Object Detection Algorithm Based on an Improved YOLOv8 by Fubin Zhang, Weiye Cao, Jian Gao, Shubing Liu, Chenyang Li, Kun Song, Hongwei Wang

“…Due to the complexity and diversity of underwater environments, traditional object detection algorithms face challenges in maintaining robustness and detection accuracy when applied underwater. …”
Get full text

Enhanced YOLO and Scanning Portal System for Vehicle Component Detection by Feng Ye, Mingzhe Yuan, Chen Luo, Shuo Li, Duotao Pan, Wenhong Wang, Feidao Cao, Diwen Chen

“…In this paper, a novel online detection system is designed to enhance accuracy and operational efficiency in the outbound logistics of automotive components after production. …”
Get full text

Machine Learning Techniques for Enhanced Intrusion Detection in IoT Security by Hanadi Hakami, Muhammad Faheem, Majid Bashir Ahmad

“…We compared several ML and DL techniques to detect and address the most efficient one for our pipeline. …”
Get full text

Research on Surface Defect Detection of Rare-Earth Magnetic Materials Based on Improved SSD by Bin Zhang, Shuqi Fang, Zhixi Li

Get full text

YOLO-Dynamic: A Detection Algorithm for Spaceborne Dynamic Objects by Haiying Zhang, Zhengyang Li, Chunyan Wang

“…This paper presents YOLO-Dynamic, a novel detection algorithm aimed at addressing the limitations of existing models, particularly in complex environments and small-object detection. …”
Get full text

MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…Due to the critical importance of one-dimensional barcode detection in logistics, retail, and manufacturing, which has become a key issue affecting operational efficiency, researchers have shown increasing interest in this area. …”
Get full text

YOLOv11-HRS: An Improved Model for Strawberry Ripeness Detection by Jianhua Liu, Jing Guo, Suxin Zhang

“…To address these problems, an efficient strawberry ripeness detection model, YOLOv11-HRS, is proposed. …”
Get full text

Multi-granularity Android malware fast detection based on opcode by Xuetao ZHANG, Meng SUN, Jinshuang WANG

“…The detection method based on opcode is widely used in Android malware detection,but it still contains some problems such as complex feature extraction method and low efficiency.In order to solve these problems,a multi-granularity fast detection method based on opcode for Android malware was proposed.Multi-granularity refers to the feature based on the bag of words model,and with the function as basic unit to extract features.By step-by-level aggregation feature,the APK multi-level information is obtained.The log length characterizes the scale of the function.And feature can be compressed and mapped to improve the efficiency and construct the corresponding classification model based on the semantic similarity of the Dalvik instruction set.Tests show that the proposed method has obvious advantages in performance and efficiency.…”
Get full text

Method for Detecting Tiny Defects on Machined Surfaces of Mechanical Parts Based on Object Recognition by Haotian Li, Zhen Wang, Lipeng Qiu, Xichu Wei

“…Practical results demonstrate that this method outperforms traditional approaches in terms of missed detection rates and detection efficiency, effectively addressing the challenge of detecting complex machining surface defects, and providing a high-precision, high-efficiency defect detection solution for the mechanical part machining field.…”
Get full text

Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
Get full text

Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This study pioneers an innovative framework, using Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features, combined with a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier, to enhance the detection of DR. Inspired by principles of randomization-based learning, our approach incorporates elements of stochastic modeling within the CNN-RBF architecture to optimize feature extraction and classification, mirroring the efficiency of non-iterative training processes. …”
Get full text