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3 articles for “AdaBoost Support Vector Machine”
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Salient Region Guided Deep Network for Violence Detection in Surveillance Systems
Abstract: Abstract: It is significant to detect violent actions in video surveillance systems automatically, for example, bus stands, malls and railway stations. Though, the earlier detection techniques generally extract statistic features around the spatiotemporal interest points or extract descriptor in the regions where movement takes place, leading to limited abilities to successfully detect violence activities in video surveillance systems. To solve this problem, a new approach for the automatic detection of …
Published in Journal of Computer Technology & Applications · Vol. 10, Issue 3, 2019 · pp. 19–28 Read article
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Prediction of Prostate Cancer Using Boosting Technique
Abstract: There are many diseases that are associated with humans, but some diseases might be associated with only males or only females. This paper shows and discusses the disorder that is associated mainly in men. Prostate cancer is associated with the example of illness. Usually when the damaged cells develop in the prostate gland occurs prostate cancer occurs. These cells increase uncontrollably. Reports given by the researchers show that this is …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 1–9 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article