Egg appearance quality detection based on CNN-SVM model by QI Ge, ZHAO Feng, LI Wanning

“…ObjectiveIn order to improve the accuracy of egg appearance quality detection, an egg appearance quality detection model based on CNN-SVM model was established.MethodsCombined with the adaptive feature extraction capability of CNN and the super-generalization classification capability of SVM, the features of fully connected layers were extracted by six-layer convolutional neural network structure processing, and the CNN-SVM hybrid model was adopted, instead of the traditional CNN + softmax, an egg appearance quality detection method based on CNN-SVM model was proposed.ResultsCompared with SVM model, CNN model and KNN model, CNN-SVM model had better performance in accuracy, precision, recall and F1 score, which were 97.97%, 98.10%, 98.10% and 98.00% respectively. …”
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Advancing food security: The role of machine learning in pathogen detection by Helen Onyeaka, Adenike Akinsemolu, Taghi Miri, Nnabueze Darlington Nnaji, Clinton Emeka, Phemelo Tamasiga, Gu Pang, Zainab Al-sharify

“…This paper reviews current advances and the application of machine learning in real-time foodborne pathogen detection and risk assessment. ML accelerates pathogen identification processes by leveraging AI-biosensing and deep learning models, significantly reducing detection times and potentially increasing accuracy rates, as indicated in several studies. …”
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Circle Detection with Adaptive Parameterization: A Bottom-Up Approach by Lin Han, Yan Zhuang, Ke Chen, Yuhua Xie, Guoliang Liao, Guangfu Yin, Jiangli Lin

“…The algorithm implements a local stochastic sampling strategy integrated with a bottom-up circular search mechanism, with all critical parameters in the algorithm derived adaptively based on λ and K, eliminating the need for repetitive hyperparameter search processes. Experiments demonstrate that our methodology achieves an exceptional Fscore of 85.5% on the public circle detection dataset, surpassing state-of-the-art approaches by approximately 7.3%. …”
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Autonomous Driving Road Environment Recognition with Multiscale Object Detection by Jeny J.R.V., Divya Phulari, Varsha Kolanu, Mrunalini Anantha, Irfan S.K.M.

“…Modern object detection frameworks allow for the accurate and efficient processing of a wide range of things that are met on the road, such as cars, bikes, pedestrians, and traffic signals. …”
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A Survey of Data Stream-Based Intrusion Detection Systems by Rodrigo Sanches Miani, Gustavo Di Giovanni Bernardo, Guilherme Weigert Cassales, Hermes Senger, Elaine Ribeiro de Faria

“…Detecting malicious activities in network environments poses a challenge that attracts significant attention due to its complexity and importance. …”
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Threshold detection by fitting segmented regression models in Microsoft Excel by Amy J Hopper, Angus M Brown

“…The method is ideal for rapid processing of data and sufficiently flexible to allow for modifications to functions when required.…”
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Deep learning in defects detection of PV modules: A review by Katleho Masita, Ali Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…Traditional manual inspection methods are time-consuming, labor-intensive, and subject to human error, necessitating the development of automated, efficient detection techniques. With the increasing scale of PV power plants, there is a pressing need for automated, accurate, and efficient defect detection methods. …”
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Overhead Analysis and Evaluation of Approaches to Host-Based Bot Detection by Yuede Ji, Qiang Li, Yukun He, Dong Guo

“…Host-based bot detection approaches discover malicious bot processes by signature comparison or behavior analysis. …”
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Pharmacological Properties of Synthetic Cannabinoids, Specifics of Their Detection and Forensic Examination by O. M. Serdega

“…The article evaluates the applicability of instrumental analysis techniques for the qualitative identification and quantitative determination of target compounds, especially in the presence of masking agents or interfering processes during sample preparation and analysis. …”
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Novel Multimodal Fusion Algorithm for Non-Intrusive Anxiety Detection by Mahir Shadid, Mushfiqus Salehin Afnan, Rashed Mustafa, M. Jamshed Alam Patwary

“…Early detection of anxiety disorders in a non-intrusive manner is crucial, as these conditions can profoundly impact an individual’s health and daily functioning. …”
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Application of Machine Learning for Real-Time Phishing Attack Detection by Akshay Shankar Agrawal, Sanketi Raut, Andrina Dsouza, Jimit Mehta, Prajwal Naik

“…This paper outlines the development and implementation of a platform to detect phishing websites. It highlights the pressing need for early detection of possible phishing attacks to prevent data theft, frauds, etc. …”
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Lightweight Domestic Pig Behavior Detection Based on YOLOv8 by Kaining Zhang, Yu Zhang, Hongli Xu

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Gas detection technology for thermal runaway of lithium-ion batteries by Yihua Qian, Yaohong Zhao, Zhi Li, Qing Wang, Yifeng Zhao

“…This paper presents a comprehensive review of gas detection and early warning technologies for lithium‐ion battery thermal runaway a critical safety concern in modern energy storage and electric vehicle applications. …”
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Modeling an Image Clustering Algorithm For Detecting Overheated Railway Axle by Oleksandr Gertsiy, Serhii Karnatov, Vitaliy Gladish, Valentyna Tkachenko

“… This paper presents an approach to image identification based on a clustering algorithm for detecting the thermal characteristics of railway axle boxes. …”
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Detection of Foodborne Viruses in Dates Using ISO 15216 Methodology by Philippe Raymond, Roxanne Blain, Neda Nasheri

“…Ready-to-eat (RTE) low moisture foods (LMFs) undergo minimal pathogen reduction processes. In recent years, multiple foodborne HAV outbreaks involving hundreds of individuals were associated with the consumption of dates, indicating that they could be important vehicles for foodborne infection. …”
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Support Vector Machine (SVM) for Tomato Leaf Disease Detection by Shafaf Ibrahim, Nur Afiqah Mohd Fuad, Nor Azura Md Ghani, Raihah Aminuddin, Budi Sunarko

“…This study proposes a method for detecting tomato leaf diseases using image processing techniques. …”
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Detection of cervical cell based on multi-scale spatial information by Gang Li, Xinyu Fan, Chuanyun Xu, Pengfei Lv, Ru Wang, Zihan Ruan, Zheng Zhou, Yang Zhang

“…To tackle this problem effectively, we propose a cervical cell detection method that utilizes multi-scale spatial information. …”
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Frobenius deep feature fusion architecture to detect diabetic retinopathy by C. Priyadharsini, Y. Asnath Victy Phamila

“…Abstract Purpose Diabetic retinopathy is a medical complication affecting the retina of patients prone to prolonged periods of Diabetes mellitus. Early detection and diagnosis are essential since the symptoms are subtle at the early stages. …”
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AnomLite: Efficient binary and multiclass video anomaly detection by Anna K. Zvereva, Mariam Kaprielova, Andrey Grabovoy

“…Anomaly detection in video surveillance is critical for ensuring public safety, as manual monitoring of numerous video feeds is often challenging and prone to human error. …”
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Detection of the Interdependence of Economic Development and Environmental Performance at the Industry Level by Nina Ilysheva, Elena Karanina, Elena Baldesku, Ulugbek Zakirov

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