Parking space number detection with multi‐branch convolution attention by Yifan Guo, Jianxun Zhang, Yuting Lin, Jie Zhang, Bowen Li

“…Since no scholar has proposed a high‐performance method for such problems, a parking space number detection model based on the multi‐branch convolutional attention is presented. …”
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Pig Detection Algorithm Based on Sliding Windows and PCA Convolution by Longqing Sun, Yan Liu, Shuaihua Chen, Bing Luo, Yiyang Li, Chunhong Liu

“…In order to solve the problems of low computational efficiency and low precision in pig detection algorithm based on sliding windows, this paper proposed a simple and efficient pig detection algorithm. …”
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A Method for Detecting Tomato Maturity Based on Deep Learning by Song Wang, Jianxia Xiang, Daqing Chen, Cong Zhang

“…Therefore, in this study, an improved YOLOv8 algorithm is proposed to address the problem of tomato fruit ripeness detection in complex scenarios, which is difficult to carry out accurately. …”
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A cascaded autoencoder unmixing network for Hyperspectral anomaly detection by Kun Li, Yingqian Wang, Qiang Ling, Yaoming Cai, Yao Qin

“…However, since abundance feature extraction and anomaly detection are decoupled, the learned features are not well-suitable for the subsequent detection. …”
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Interaction based on method for spam detection in online social networks by Kan CHEN, Liang CHEN, Pei-dong ZHU, Yue-shan XIONG

“…In online social networks,advertisements,rumors and malicious links are propagated by spammers arbitrarily.They not only disturb users’usualaccess,but also bring about network security threats and social panics.In an attempt to deal with the spam problems,an information diffusion model was proposed to capture the features of spam propagation.Propagation behaviors are quantitatively analyzed to detect spam messages with a decision tree-based method.The effectiveness of proposed detection model is evaluated with real data from the micro-bloggingnetwork of Sina.The experimental results show that proposed model can effectively detect spams in Sina micro-bloggingnetwork.…”
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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.…”
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Blotch Detection in Archive Films Based on Visual Saliency Map by Yildiz Aydin, Bekir Dizdaroğlu

“…Degradations frequently occur in archive films that symbolize the historical and cultural heritage of a nation. In this study, the problem of detection blotches commonly encountered in archive films is handled. …”
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Deep encoder-decoder networks for belt longitudinal tear detection by Lei You, Minghua Luo, Xinglin Zhu, Bin Zhou

“…An improved encoder-decoder network was proposed to solve the longitudinal tear detection problem. This method utilizes a line structured light system for image acquisition. …”
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An Approach Based on Sum Product Networks for Code Smells Detection by Mostefai Abdelkader

“…Thus, many approaches have been proposed to detect and manage them. However, detecting code smells remains a challenging problem. …”
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Dysarthria Severity detection Using Recurrent and Convolutional Neural Networks by Amina Hamza, Djamel Addou

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Cherry defect and classification detection based on improved YOLOX model by LIU Jing-yu, PEI Yue-kun, CHANG Zhi-yuan, CHAI Zhi, CAO Pei-pei

“…The detection accuracy of the inconspicuous defect was improved by setting the appropriate fusion factor for the feature pyramid network, and in order to solve the problem of imbalance between various types of real samples, Focal Loss was integrated into the loss function. …”
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Machine Learning Techniques for Enhanced Intrusion Detection in IoT Security by Hanadi Hakami, Muhammad Faheem, Majid Bashir Ahmad

“…Therefore, it is necessary to find an efficient method for solving the problem by using classification with an intrusion detection system which analyzes enormous amounts of traffic data. …”
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The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Traditional fraud detection methods based on rules and statistical analysis are difficult to deal with increasingly complex and evolving fraud methods, and there are problems such as poor adaptability and high false alarm rate. …”
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Target Tracking Algorithm Based on Adaptive Scale Detection Learning by Dawei Yang

“…In this paper, to better solve the problem of low tracking accuracy caused by the sudden change of target scale, we design and propose an adaptive scale mutation tracking algorithm using a deep learning network to detect the target first and then track it using the kernel correlation filtering method and verify the effectiveness of the model through experiments. …”
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Detection and monitoring of stress using wearables: a systematic review by Anuja Pinge, Vinaya Gad, Dheryta Jaisighani, Surjya Ghosh, Sougata Sen

“…One health-related area that has rapidly adopted wearable devices is the mental health monitoring and well-being area, which covers problems such as psychological distress. The continuous monitoring capability of wearable devices allows the detection and monitoring of stress, thus enabling early detection of mental health problems. …”
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Two-stage Detection Method for Abnormal Cluster Cervical Cells by LIANG Yi-qin, ZHAO Si-qi, WANG Hai-tao, HE Yong-jun

“…Cells adhere to each other, complex and diverse, which brings challenges to abnormal cell detection. To solve this problem, we proposed a two-stage detection method for cluster cervical abnormal cells. …”
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Intelligent detection method on network malicious traffic based on sample enhancement by Tieming CHEN, Chengqiang JIN, Mingqi LYU, Tiantian ZHU

“…To address the problem that the existing methods of network traffic anomaly detection not only need a large number of training sets,but also have poor generalization ability,an intelligent detection method on network malicious traffic based on sample enhancement was proposed.The key words were extracted from the training set and the sample of the training set was enhanced based on the strategy of key word avoidance,and the ability for the method to extract the text features from the training set was improved.The experimental results show that,the accuracy of network traffic anomaly detection model and cross dataset can be significantly improved by small training set.Compared with other methods,the proposed method can reduce the computational complexity and achieve better detection ability.…”
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Efficient Intrusion Detection System for SDN Orchestrated Internet of Things by Esubalew M. Zeleke, Henock M. Melaku, Fikreselam G. Mengistu

“…It is an important technology that is aimed to solve the different problems existing in the traditional network systems. …”
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Object Detection Method of Inland Vessel Based on Improved YOLO by Yaoqi Wang, Jiasheng Song, Yichun Wang, Rongjie Wang, Hongyu Chen

“…In order to solve the problems of low accuracy of the current mainstream target detection algorithms in identifying small target ships, complex background interference such as coastline buildings and trees, and the influence of ship occlusion on ship target detection, an inland river ship detection method based on improved YOLOv10n: CDS-YOLO is proposed under the premise of keeping the model lightweight. …”
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Traffic sign detection method based on improved YOLOv8 by Gaihua Wang, Peng Jin, Zhiwei Qi, Xiaohuan Li

“…Aiming at the current traffic sign detection problems of leakage, misdetection and low detection accuracy of small targets, a traffic sign detection method based on improved YOLOv8n is proposed. …”
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