The Effect of Using Computerized Financial Statement Analysis on the Efficiency of Financial Performance: An Empirical Case on Industrial Factor in Project Scheduling-Jordan Case S... by Atallah Alhosban, Fedel Al-Habashneh, George Shawaqfeh, Essa Al-Tarawneh

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MSAN-Net: An End-to-End Multi-Scale Attention Network for Universal Industrial Defect Detection by Zelu Wang, Ming Luo, Xinghe Xie, Yue Sun, Xinyu Tian, Zhengxuan Chen, Junwei Xie, Qinquan Gao, Tong Tong, Yue Liu, Tao Tan

“…Traditional manual visual inspection or single-task deep learning models were often struggled to balance detection efficiency and accuracy in complex industrial scenarios. …”
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Fast Quality Detection of <i>Astragalus</i> Slices Using FA-SD-YOLO by Fan Zhao, Jiawei Zhang, Qiang Liu, Chen Liang, Song Zhang, Mingbao Li

“…Additionally, the integration of the SD module into the detection head optimizes parameter efficiency while improving detection performance. …”
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Ground-Independent UAV Quantitative Mapping and In Situ Experimental Validation for Coral Reef Habitats by Enze Wang, Huaguo Zhang, Yunhan Ma, Han Tong, Juan Wang, Wenting Cao, Dongling Li

“…Optically shallow waters, which host ecosystems like coral reefs, are characterized by complex radiative transfer pathways. Surface reflectance derived from remote sensing in optically shallow waters is influenced by water depth, water quality, and bottom reflectance. …”
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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…The GSF-YOLOv8 not only significantly improves the efficiency and accuracy of fire detection but also provides a more reliable and accurate solution for real-time detection in similarly complex environments.…”
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Research on anomaly detection model for traffic time series data integrating multiple mechanisms by Peipei ZHANG, Jiaqi LIU

“…The results show that adding each module on the basis of LSTM significantly improves the model's prediction and anomaly detection ability; Compared with the general hybrid model Transformer-Bi-LSTM, the proposed model has stronger prediction ability and lower computational complexity. …”
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Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model by Yuan Liu, Yilong Liu, Xiaoyan Guo, Xi Ling, Qingyi Geng

“…On the AL10-DET dataset, SLF-YOLO achieves a mAP of 86.8%, striking an effective balance between detection accuracy and computational efficiency without increasing model complexity. …”
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Ambient Intelligence to Detect Misuse of Electricity Consumption Based on IoT Using Blockchain Technology by Soiful Hadi, Wahyul Amien Syafei, Adi Wibowo

“…Electricity abuse and energy inefficiencies are still open issues in smart grid systems, demanding high-performance anomaly detection mechanisms. In this paper, we propose an IoT-enabled electricity monitoring system that combines machine learning (LightGBM) and blockchain (Polygon network) for real-time anomaly detection, secure data storage, and transparent energy tracking. …”
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An Improved Unmanned Aerial Vehicle Forest Fire Detection Model Based on YOLOv8 by Bensheng Yun, Xiaohan Xu, Jie Zeng, Zhenyu Lin, Jing He, Qiaoling Dai

“…Taking into account efficiency and cost-effectiveness, deep-learning-driven UAV remote sensing fire detection algorithms have emerged as a favored research trend and have seen extensive application. …”
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Target detection of helicopter electric power inspection based on the feature embedding convolution model. by Dakun Liu, Wei Zhou, Linzhen Zhou, Wen Guan

“…In addition, this study further optimizes the model with reinforcement learning technology, conducts a comparative analysis of different flight environments and facilities, and reveals the diversity and complexity of inspection objectives. The performance of the optimized model in fault detection is increased by more than 36%. …”
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Surface anomaly detection on island-based PV panels using edge neural networks by ZHANG Yinxian, ZHANG Zhanyao, ZHANG Xiya

“…Due to the poor accuracy and low efficiency of existing detection methods， the paper proposes a surface anomaly detection method for island-based PV panels using edge neural networks. …”
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A lightweight model for echo trace detection in echograms based on improved YOLOv8 by Jungang Ma, Jianfeng Tong, Minghua Xue, Junfan Yao

“…However, current detection models are too parameter-heavy to embed in echosounders and struggle with noisy, irregular, and dense echograms. …”
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Combination of Principal Component Analysis and Time-Frequency Representation for P-Wave Arrival Detection by Jacek Wodecki, Justyna Hebda-Sobkowicz, Adam Mirek, Radosław Zimroz, Agnieszka Wyłomańska

“…Due to the significant difference between the spectra of recorded seismic wave and pure noise which precedes the event, time-frequency representation allows for better accuracy of signal change detection. However, with an additional domain, the complexity rises. …”
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Leveraging Swarm Intelligence for Invariant Rule Generation and Anomaly Detection in Industrial Control Systems by Yunkai Song, Huihui Huang, Hongmin Wang, Qiang Wei

“…Conventional anomaly detection techniques often lack the ability to provide clear explanations for their detection, and their inherent complexity can impede practical implementation in the resource-constrained environments typical of ICSs. …”
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SmartRipen: LSTM-GRU feature selection& XGBoost-CNN for fruit ripeness detection by Archana Ganesh Said, Bharti Joshi

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Hybrid Wavelet-Attention Model for Detecting Changes in High-Resolution Remote Sensing Images by Lhuqita Fazry, MGS M. Luthfi Ramadhan, Alif Wicaksana Ramadhan, Muhammad Febrian Rachmadi, Aprinaldi Jasa Mantau, Lukito Edi Nugroho, Chi-Hung Chi, Wisnu Jatmiko

“…However, this causes information loss, resulting in a trade-off between the effectiveness and efficiency of the method. To solve the problem, we developed a new change detection method called WaveCD. …”
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Detecting command injection attacks in web applications based on novel deep learning methods by Xinyu Wang, Jiqiang Zhai, Hailu Yang

“…Abstract Web command injection attacks pose significant security threats to web applications, leading to potential server information leakage or severe server disruption. Traditional detection methods struggle with the increasing complexity and obfuscation of these attacks, resulting in poor identification of malicious code, complicated feature extraction processes, and low detection efficiency. …”
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Enhancing Software Quality with AI: A Transformer-Based Approach for Code Smell Detection by Israr Ali, Syed Sajjad Hussain Rizvi, Syed Hasan Adil

“…In this study, we introduce Relation-Aware BERT (RABERT), a novel transformer-based model that integrates relational embeddings to enhance automated code smell detection. By modeling interdependencies among software complexity metrics, RABERT surpasses classical machine-learning methods, achieving an accuracy of 90.0% and a precision of 91.0%. …”
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Real-Time Power System Event Detection: A Novel Instance Selection Approach by Gabriel Intriago, Yu Zhang

“…This study presents a novel adaptation of the Hoeffding Adaptive Tree (HAT) classifier with an instance selection algorithm that detects and identifies cyber and non-cyber contingencies in real time to enhance the situational awareness of cyber-physical power systems (CPPS). …”
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Can YOLO Detect Retinal Pathologies? A Step Towards Automated OCT Analysis by Adriana-Ioana Ardelean, Eugen-Richard Ardelean, Anca Marginean

“…Through the advancement of technology, the volume and complexity of OCT data have rendered manual analysis infeasible, creating the need for automated means of detection. …”
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