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

DCFE-YOLO: A novel fabric defect detection method. by Lei Zhou, Bingya Ma, Yanyan Dong, Zhewen Yin, Fan Lu

“…However, the task of fabric defect detection remains highly challenging due to the complex textures and diverse defect patterns. …”
Get full text

Lightweight highland barley detection based on improved YOLOv5 by Minghui Cai, Hui Deng, Jianwei Cai, Weipeng Guo, Zhipeng Hu, Dongzheng Yu, Houxi Zhang

“…In addition,the proposed model outperformed mainstream object detection algorithms such as Faster R-CNN, Mask R-CNN, RetinaNet, YOLOv7, and YOLOv8, in terms of detection accuracy and computational efficiency. …”
Get full text

Contrastive learning of cross-modal information enhancement for multimodal fake news detection by Weijie Chen, Fei Cai, Yupu Guo, Zhiqiang Pan, Wanyu Chen, Yijia Zhang

Get full text

Deep learning algorithms for detecting fractured instruments in root canals by Ekin Deniz Çatmabacak, İrem Çetinkaya

“…Conclusions DenseNet201’s superior performance highlights its clinical potential for FEI detection, while ResNet-18 offers a balance between accuracy and computational efficiency. …”
Get full text

(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…Abstract To address the complex requirements of network intrusion detection in IoT environments, this study proposes a hybrid intelligent framework that integrates the Whale Optimization Algorithm (WOA) and the Grey Wolf Optimization (GWO) algorithm—referred to as WOA-GWO. …”
Get full text

A Method for Detecting Tomato Maturity Based on Deep Learning by Song Wang, Jianxia Xiang, Daqing Chen, Cong Zhang

“…The algorithm employs several technical means to improve detection accuracy and efficiency. First, Swin Transformer is used to replace the third C2f in the backbone part. …”
Get full text

DWS-YOLO: A Lightweight Detector for Blood Cell Detection by Yihai Mao, Hongyi Zhang, Wanqing Wu, Xingen Gao, Zhibin Lin, Juqiang Lin

“…Our objective is to construct an efficient deep learning model for peripheral blood cell analysis that achieves an optimized balance between inference speed, computational complexity, and detection accuracy. …”
Get full text

A streamlined POCT solution for rapid infectious disease detection by Yaping Xie, Yan Yu, Shuaiwu Huang, Liangcheng Wan, Chang Wu, Chiwei Yin, Jianjun Li, Jiangang Ling, Lizhong Dai

“…Abstract Point-of-care testing (POCT) plays a crucial role in infectious disease screening due to its rapid detection and portability. However, current POCT systems face challenges such as lengthy sample preparation time, complex nucleic acid extraction, and limited real-time data transmission, extending patient waiting time. …”
Get full text

Implementation of YOLOv7 Model for Human Detection in Difficult Conditions by Arijal B, Andi Sunyoto, M. Hanafi

“…The rapid development of artificial intelligence technology in recent decades has led to the development of highly efficient object detection algorithms, including human detection under difficult conditions. …”
Get full text

MODEL BASED FAULT DETECTION FOR SAFETY MANAGEMENT OF THE INDUSTRIAL PROCESSES by Dumitru POPESCU, Pierre BORNE, Crina TOROUS

“…Detection and diagnosis are important actions offered by the complex automations, that contribute to keeping the exploitation of the process safe. …”
Get full text

D-YOLO: A Lightweight Model for Strawberry Health Detection by Enhui Wu, Ruijun Ma, Daming Dong, Xiande Zhao

“…In complex agricultural settings, accurately and rapidly identifying the growth and health conditions of strawberries remains a formidable challenge. …”
Get full text

Crack Detection on Road Surfaces Based on Improved YOLOv8 by Haiyang Wu, Lingyun Kong, Denghui Liu

“…Road defect detection is vital for road maintenance but remains challenging due to the complexity of backgrounds, low resolution, and crack similarity. …”
Get full text

Building Surface Defect Detection Based on Improved YOLOv8 by Xiaoxia Lin, Yingzhou Meng, Lin Sun, Xiaodong Yang, Chunwei Leng, Yan Li, Zhenyu Niu, Weihao Gong, Xinyue Xiao

“…In intelligent building, efficient surface defect detection is crucial for structural safety and maintenance quality. …”
Get full text

Evaluating Lightweight Transformers With Local Explainability for Android Malware Detection by Fatima Bourebaa, Mohamed Benmohammed

“…The findings demonstrate the viability of lightweight transformers for near-real-time Android malware detection, balancing accuracy, efficiency, and interpretability.…”
Get full text

Advanced Nanoformulations for Detection and Removal of Poly- and Perfluoroalkyl Substances (PFAS) by Jyotish Kumar, Mahesh Narayan

“…The conventional, highly sensitive methods used for PFAS detection are LC-MS/MS and solid phase extraction, but they are very complex and expensive. …”
Get full text