Target Detection Technology of Mechanical, Electrical, and Plumbing Components Based on CV by Guohua Wei, Ding Zhou, Xiaojun Yuan

“…The proposed architecture addresses the limitations of existing techniques in handling MEP complexities, and through an automatic comparison and verification process, it detects deviations promptly, ensuring adherence to design specifications. …”
Get full text

Steel surface defect detection method based on improved YOLOv9 by Cong Chen, Hoileong Lee, Ming Chen

“…To address this issue, this paper proposes an improved steel surface defect detection algorithm based on YOLOv9. First, introducing Depthwise Separable Convolution (DSConv) can effectively reduce the computational complexity of the model, thereby enhancing its operational efficiency. …”
Get full text

AI-Based Anomaly Detection and Optimization Framework for Blockchain Smart Contracts by Hassen Louati, Ali Louati, Elham Kariri, Abdulla Almekhlafi

“…However, the increasing complexity of these contracts introduces significant challenges, including high computational costs, scalability limitations, and difficulties in detecting anomalous behavior. …”
Get full text

Driver Distraction Detection in Extreme Conditions Using Kolmogorov–Arnold Networks by János Hollósi, Gábor Kovács, Mykola Sysyn, Dmytro Kurhan, Szabolcs Fischer, Viktor Nagy

“…The results suggest that KANs can enhance driver distraction detection under challenging conditions, with improved resilience against adversarial attacks, particularly in low-complexity networks.…”
Get full text

A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

“…Compared to other methods, our approach outperforms them in both performance and efficiency, fulfilling the real-time and precise defect detection needs of photodetectors.…”
Get full text

Optimal resource allocation for two-stage connectionless access with collision detection by Xin JIAN, Fang WANG, Jian SONG, Shu FU, Xiaoheng TAN, Xiaoping ZENG

“…Connectionless access allows massive machine type communication (mMTC) devices to transmit small packets without establishment of radio bearers,significantly reducing device power consumption and control signaling overhead.Two-stage connectionless access (TSCLA) improves throughput and resource efficiency by optimally allocating resources between scheduling request (SR) phase and data transmission phase,which can be used for bigger packets and high traffic load.Based on this,a comprehensive theoretical analysis of one kind of TSCLA with collision detection was conducted to investigate its performance limit and devise its optimal resource allocation scheme.In addition,to avoid the complexity of user number estimation,a dynamic resource allocation algorithm with feedback control was proposed.Numerical results are provided to validate the effectiveness of aforementioned theoretical results and show that comparing with the genie aided algorithm known exactly the number of users,the performance loss of the proposed algorithm is within 4%.These works together provide good references for appropriate resource dimensioning for mMTC related protocols.…”
Get full text

Lightweight network for insulator fault detection based on improved YOLOv5 by Dehua Weng, Zhiliang Zhu, Zhengbing Yan, Moran Wu, Ziang Jiang, Nan Ye

“…To address these issues, we introduce a novel one-stage network that enables real-time detection of insulator faults on mobile devices. We designed a new module that optimises the computational complexity of networks and fused the module with the attention mechanism SimAM to solve the problem of low efficiency in detecting flashover faults. …”
Get full text

TARGE: large language model-powered explainable hate speech detection by Muhammad Haseeb Hashir, Memoona, Sung Won Kim

“…The proliferation of user-generated content on social networking sites has intensified the challenge of accurately and efficiently detecting inflammatory and discriminatory speech at scale. …”
Get full text

Multi-defect detection and classification for aluminum alloys with enhanced YOLOv8. by Ying Han, Xingkun Li, Gongxiang Cui, Jie Song, Fengyu Zhou, Yugang Wang

“…Experimental results show that the proposed method performs effectively in target detection and classification. The number of model parameters is reduced from more than 300,000 to 160,000, significantly reducing the complexity of the model. …”
Get full text

Copper Nodule Defect Detection in Industrial Processes Using Deep Learning by Zhicong Zhang, Xiaodong Huang, Dandan Wei, Qiqi Chang, Jinping Liu, Qingxiu Jing

“…The surface of cathodic copper plates is often affected by various electrolytic process factors, resulting in the formation of nodule defects that significantly impact surface quality and disrupt the downstream production process, making the prompt detection of these defects essential. At present, the detection of cathode copper plate nodules is performed by manual identification. …”
Get full text

Lightweight Pepper Disease Detection Based on Improved YOLOv8n by Yuzhu Wu, Junjie Huang, Siji Wang, Yujian Bao, Yizhe Wang, Jia Song, Wenwu Liu

Get full text

Detecting faults in electronic combustion engine control systems by acoustic parameters by V. D. Gabidulin, V. N. Dobromirov

Get full text

AFENet: An Attention-Focused Feature Enhancement Network for the Efficient Semantic Segmentation of Remote Sensing Images by Jiarui Li, Shuli Cheng

“…The semantic segmentation of high-resolution remote sensing images (HRRSIs) faces persistent challenges in handling complex architectural structures and shadow occlusions, limiting the effectiveness of existing deep learning approaches. …”
Get full text

Research and optimization of a multilevel fire detection framework based on deep learning and classical pattern recognition techniques by Qi Liu, Hong Chen, Da Lin

“…Despite advancements in both traditional methodologies and modern deep learning models, challenges such as suboptimal accuracy and elevated false alarm rates persist, particularly in complex environmental scenarios. This paper introduces the Fire Focused Detection Network (FFDNet), a state-of-the-art flame detection framework that seamlessly integrates classical approaches with deep learning strategies. …”
Get full text

Harnessing artificial intelligence for efficient systematic reviews: A case study in ecosystem condition indicators by Isabel Nicholson Thomas, Philip Roche, Adrienne Grêt-Regamey

“…We show that, although not completely infallible, the GPT-3.5 model significantly outperforms traditional literature screening processes in terms of speed and efficiency whilst correctly selecting 83 % of relevant literature for review. …”
Get full text

Efficient network attack path optimization method based on prior knowledge-based PPO algorithm by Qiuxiang Li, Jianping Wu

“…Through this approach, the action space is effectively pruned, thereby enhancing the performance and efficiency of the algorithm in large-scale, complex network scenarios. …”
Get full text

LiteTom-RTDETR: A Lightweight Real-Time Tomato Detection System for Plant Factories by Wenshuai Liu, Qingzheng Liu, Wenyong Quan, Junli Wang, Xiaomin Yao, Qiang Liu, Yuxiang Tian

“…The proposed LiteTom-RTDETR model was shown to balance high tomato identification accuracy (88.2%) with an excellent real-time inference speed (52.2 frames per second) and computational efficiency (36.3 GFLOPs). Notably, the average detection accuracy of LiteTom-RTDETR was 0.6% higher, its detection speed was 15.5% faster, and its computational load and model size were 36.2% and 31.6% smaller, respectively, than those of the original RTDETR model. …”
Get full text

Wavelet-Analysis of Cardiosignals Using Matlab by B. F. Badalyan, H. A. Gomtsyan, S. G. Gomtsyan

“…This article is devoted to the problem of accurate detection of cardiosignal QRS-complexes for early diagnosis of various diseases of human cardiovascular system. …”
Get full text

RRBM-YOLO: Research on Efficient and Lightweight Convolutional Neural Networks for Underground Coal Gangue Identification by Yutong Wang, Ziming Kou, Cong Han, Yuchen Qin

“…Coal gangue identification is the primary step in coal flow initial screening, which mainly faces problems such as low identification efficiency, complex algorithms, and high hardware requirements. …”
Get full text

Dynamics-based predictions of infinite-dimensional complex systems using dynamical system deep learning method by Hao Li, Jianping Li, Zixiang Wu, Mingyu Wang, Guangcan Liu, Ruipeng Sun, Ruize Li, Ning Wang, Houbin Song, Shixin Zhen

“…Predicting complex nonlinear chaotic dynamical systems constitutes a critical and formidable challenge across various disciplines. …”
Get full text