A Transfer-Learning-Based Approach for Emergency Vehicle Detection

Intrusion Detection based on a Novel Hybrid Learning Approach

Information security and Intrusion Detection System (IDS) plays a critical role in the Internet. IDS is an essential tool for detecting different kinds of attacks in a network and maintaining data integrity, confidentiality and system availability against possible threats. In this paper, a hybrid approach towards achieving high performance is proposed. In fact, the important goal of this paper ...

A Vehicle Detection Approach using Deep Learning Methodologies

The purpose of this study is to successfully train our vehicle detector using R-CNN, Faster R-CNN deep learning methods on a sample vehicle data sets and to optimize the success rate of the trained detector by providing efficient results for vehicle detection by testing the trained vehicle detector on the test data. The working method consists of six main stages. These are respectively; loading...

A Prior-based Transfer Learning Method for the Phishing Detection

In this paper, we introduce a prior-based transfer learning method for our statistical machine learning classifier which based on the logistic regression to detect the phishing sites that relies on our selected features of the URLs. Because of the mismatched distributions of the features in different phishing domains, we employ multiple models for different regions. Since it is impossible for u...

A Sparse Coding Based Transfer Learning Framework for Pedestrian Detection

Pedestrian detection is a fundamental problem in video surveillance and has achieved great progress in recent years. However, training a generic detector performing well in a great variety of scenes has been approved to be very difficult. On the other hand, exhausting manual labeling effort for each specific scene to achieve high accuracy of detection is not acceptable especially for video surv...

A Matrix Factorization & Clustering Based Approach for Transfer Learning