بدائل البحث:
detection survey » detection system (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), colony algorithm (توسيع البحث), scheduling algorithm (توسيع البحث)
cnn algorithm » rd algorithm (توسيع البحث), colony algorithm (توسيع البحث), cosine algorithm (توسيع البحث)
elements cnn » elements _ (توسيع البحث)
detection survey » detection system (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), colony algorithm (توسيع البحث), scheduling algorithm (توسيع البحث)
cnn algorithm » rd algorithm (توسيع البحث), colony algorithm (توسيع البحث), cosine algorithm (توسيع البحث)
elements cnn » elements _ (توسيع البحث)
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CNN and HEVC Video Coding Features for Static Video Summarization
منشور في 2022احصل على النص الكامل
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Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks
منشور في 2024"…This survey paper offers an in-depth examination of advanced machine learning (ML) and deep learning (DL) approaches employed in developing sophisticated IDS for safeguarding IVNs against potential cyber-attacks. …"
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Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey
منشور في 2024"…As new <u>malware</u> gets introduced frequently by <u>malware developers</u>, it is very challenging to come up with comprehensive algorithms to detect this malware. There are many machine-learning and deep-learning algorithms have been developed by researchers. …"
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AI-Aided Robotic Wide-Range Water Quality Monitoring System
منشور في 2024احصل على النص الكامل
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
منشور في 2020"…ML based informal diagnostic and decision support systems can provide a first line of detection to alert patients about potential disease risk. …"
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Building power consumption datasets: Survey, taxonomy and future directions
منشور في 2020"…Based on the analytical study, a novel dataset has been presented, namely Qatar university dataset, which is an annotated power consumption anomaly detection dataset. The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. …"
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Automatic Video Summarization Using HEVC and CNN Features
منشور في 2022احصل على النص الكامل
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
منشور في 2025"…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …"
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Deep and transfer learning for building occupancy detection: A review and comparative analysis
منشور في 2022"…Moreover, the paper conducted a comparative study of the readily available algorithms for occupancy detection to determine the optimal method in regards to training time and testing accuracy. …"
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A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques
منشور في 2022"…Amongst the range of classification algorithms, support vector machines (SVMs) are heavily utilised for detecting phishing emails. …"
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احصل على النص الكامل
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Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
منشور في 2021"…Specifically, an extensive survey is presented, in which a comprehensive taxonomy is introduced to classify existing algorithms based on different modules and parameters adopted, such as machine learning algorithms, feature extraction approaches, anomaly detection levels, computing platforms and application scenarios. …"
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
منشور في 2023"…The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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