Non-Destructive Detection of Fruit Quality: Technologies, Applications and Prospects by Jingyi Liu, Jun Sun, Yasong Wang, Xin Liu, Yingjie Zhang, Haijun Fu

“…These technologies can detect a variety of chemical components of fruit, realize the assessment of maturity, damage degree, disease degree, and are suitable for orchard picking, quality grading, shelf life prediction and other fields. …”
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Artificial intelligence-based detection of dens invaginatus in panoramic radiographs by Ayse Hanne Sarı, Hasan Sarı, Guldane Magat

“…Abstract Objective The aim of this study was to automatically detect teeth with dens invaginatus (DI) in panoramic radiographs using deep learning algorithms and to compare the success of the algorithms. …”
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AI-enhanced fire detection and suppression system for autonomous ships by Hyuk Lee, Jung Hoon Chung, Hyun Chung, Jong-Hwan Kim, Yongho Yoo, Gil Hyuk Lim, Won-Sun Ruy

“…Meanwhile, the shipping industry faces crew shortages, making unmanned fire detection crucial for reducing manpower while ensuring seamless operations. …”
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Road Damage Detection Using Yolov9-Based Imagery by Febrian Akbar Azhari, Tatang Rohana, Kiki Ahmad Baihaqi, Ahmad Fauzi

“…This study aims to develop an effective method for detecting road damage, utilizing the YOLOv9 algorithm as a key component, such as cracks and potholes, using the Convolutional Neural Network (CNN) approach. …”
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Effectively Detecting Communities by Adjusting Initial Structure via Cores by Mei Chen, Zhichong Yang, Xiaofang Wen, Mingwei Leng, Mei Zhang, Ming Li

“…In this paper, we propose a simple but effective community detection algorithm, called ACC, which needs no heuristic search but has near-linear time complexity. …”
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Computational approaches to apply the String Edit Algorithm to create accurate visual scan paths by Ricardo Palma Fraga, Ziho Kang

“… Eye movement detection algorithms (e.g., I-VT) require the selection of thresholds to identify eye fixations and saccadic movements from gaze data. …”
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A Distributed Optimization Algorithm for Energy of Wireless Sensor Networks Based on Potential Game by Lingfeng Shao, Junjie Yang, Jicheng Fang

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Three-Dimensional Autonomous Obstacle Avoidance Algorithm for UAV Based on Circular Arc Trajectory by Jiandong Guo, Chenyu Liang, Kang Wang, Biao Sang, Yulin Wu

“…Then, on the basis of the geometric relationship between a UAV and obstacle modeling, the working mechanism of the avoidance algorithm is developed. The rules of obstacle detection, avoidance direction, and the criterion of avoidance success are defined for different obstacle types. …”
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Calibration and uncertainty quantification for deep learning-based drought detection by Mengxue Zhang, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Gustau Camps-Valls

“…To address this shortcoming, we introduce methodologies for model calibration and entropy-based uncertainty quantification for deep learning-based drought detection. The calibration algorithm can deal with calibration errors by reducing distributional shifts and alleviating overconfident predictions. …”
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Research Progress on Non-destructive Detection Techniques for Potatoes Quality by YANG Guang-hui, LI Hong-ling, ZHANG Hua, LI Hui, LIU Xiao-long, JIA Shang-yun, HU Bo, SHANG Yi-bo

“…Through research and analysis, the problems facing non-destructive detection technology for potato quality were proposed, and prospects for the selection of imaging systems, multimodal detection technology, algorithm optimization, and intelligent detection technology were discussed, which could provide a reference for in-depth research and practical application of non-destructive detection technology for potato quality.…”
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Detecting phishing gangs via taint analysis on the Ethereum blockchain by Kangrui Huang, Weili Chen, Zibin Zheng

“…Based on this, we propose a heuristics algorithm for phishing gang detection. And we also summarize gang patterns and reveal money laundering in phishing activities. …”
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Detection of Wild Mushrooms Using Machine Learning and Computer Vision by Christos Chaschatzis, Chrysoula Karaiskou, Chryssanthi Iakovidou, Panagiotis Radoglou-Grammatikis, Stamatia Bibi, Sotirios K. Goudos, Panagiotis G. Sarigiannidis

“…The proposed approach utilises unmanned aerial vehicles (UAVs) equipped with multispectral imaging and the YOLOv5 object detection algorithm. A custom dataset, the wild mushroom detection dataset (WOES), comprising 907 annotated aerial and ground images, was developed to support model training and evaluation. …”
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Advances in Object Detection and Localization Techniques for Fruit Harvesting Robots by Xiaojie Shi, Shaowei Wang, Bo Zhang, Xinbing Ding, Peng Qi, Huixing Qu, Ning Li, Jie Wu, Huawei Yang

“…This work systematically summarizes and analyzes about 120 related literatures on the object detection and three-dimensional positioning algorithms of harvesting robots over the last 10 years, and reviews several significant methods. …”
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Hard-coded backdoor detection method based on semantic conflict by Anxiang HU, Da XIAO, Shichen GUO, Shengli LIU

“…The current router security issues focus on the mining and utilization of memory-type vulnerabilities, but there is low interest in detecting backdoors.Hard-coded backdoor is one of the most common backdoors, which is simple and convenient to set up and can be implemented with only a small amount of code.However, it is difficult to be discovered and often causes serious safety hazard and economic loss.The triggering process of hard-coded backdoor is inseparable from string comparison functions.Therefore, the detection of hard-coded backdoors relies on string comparison functions, which are mainly divided into static analysis method and symbolic execution method.The former has a high degree of automation, but has a high false positive rate and poor detection results.The latter has a high accuracy rate, but cannot automate large-scale detection of firmware, and faces the problem of path explosion or even unable to constrain solution.Aiming at the above problems, a hard-coded backdoor detection algorithm based on string text semantic conflict (Stect) was proposed since static analysis and the think of stain analysis.Stect started from the commonly used string comparison functions, combined with the characteristics of MIPS and ARM architectures, and extracted a set of paths with the same start and end nodes using function call relationships, control flow graphs, and branching selection dependent strings.If the strings in the successfully verified set of paths have semantic conflict, it means that there is a hard-coded backdoor in the router firmware.In order to evaluate the detection effect of Stect, 1 074 collected device images were tested and compared with other backdoor detection methods.Experimental results show that Stect has a better detection effect compared with existing backdoor detection methods including Costin and Stringer: 8 hard-coded backdoor images detected from image data set, and the recall rate reached 88.89%.…”
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A novel framework for Chinese personal sensitive information detection by Chenglong Ren, Xiao Lan, Xingshu Chen, Yonggang Luo, Shuhua Ruan

“…The EBC model uses the latest ELECTRA algorithm to implement word embedding, and uses BiLSTM and CRF models to extract personal sensitive information, which can detect Chinese sensitive entities accurately by analysing context information. …”
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Myocarditis Detection Using Proximal Policy Optimization and Mutual Learning by Asadi Srinivasulu, Sivaram Rajeyyagari

“…To address class imbalance, a proximal policy optimization (PPO)-based algorithm is utilized, significantly improving the training process by preventing abrupt policy shifts and stabilizing them. …”
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Improved YOLOv5: Efficient Object Detection for Fire Images by Dongxing Yu, Shuchao Li, Zhongze Zhang, Xin Liu, Wei Ding, Xinyi Zhao

“…This network utilizes the YOLOv5 algorithm. The default versions of the You Only Look Once (YOLO) technique demonstrate limited accuracy when applied to fire detection instances, even after undergoing training and testing. …”
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YOLO-WAD for Small-Defect Detection Boost in Photovoltaic Modules by Yin Wang, Wang Yun, Gang Xie, Zhicheng Zhao

“…The experimental results show that YOLO-WAD detects our dataset with an overall accuracy of 95.6%, with the small-target defect detection accuracy reaching 86.3%, which is 4.1% and 9.5% higher than YOLOv10n and current mainstream models, verifying the feasibility of our algorithm.…”
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Developing an Intelligent System for Efficient Botnet Detection in IoT Environment by Ramesh Singh Rawat, Manoj Diwakar, Umang Garg, Prakash Srivastava

“…We have also achieved a high attack detection rate.…”
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Disagreement in Detected Heatwave Trends Resulting From Diagnostic Methods by Boyuan Zhang, Yongli He, Zhanbo Wang, Bo Huang, Yongkun Xie, Xiaodan Guan, Jianping Huang

“…Here, we employed 3‐dimensional connected detection algorithm (3DCDA) to explore the dependency of heatwave identifications on various parameter combinations. …”
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