Reducing False Alarms Using Genetic Programming in Object Detection
نویسندگان
چکیده
This paper describes a refinement of an approach to locating objects in complex images with the objective of reducing the false alarm rate. The method uses genetic programming to evolve a detector using a threshold for defining an unclassified region. It is envisaged that incorporating a threshold during training will encourage programs to produce a high output when the object has been located. The objects required to be located are two difficult cephalometric landmarks that are either ambiguous in nature or located in a cluttered background. Results suggest that while increasing the threshold reduces the false alarm rate, it is to the detriment of the detection rate.
منابع مشابه
Moving Object Detection in Video Using Saliency Map and Subspace Learning
Moving object detection is a key to intelligent video analysis. On the one hand, what moves is not only interesting objects but also noise and cluttered background. On the other hand, moving objects without rich texture are prone not to be detected. So there are undesirable false alarms and missed alarms in many algorithms of moving object detection. To reduce the false alarms and missed alarms...
متن کاملA Lightweight Intrusion Detection System Based on Specifications to Improve Security in Wireless Sensor Networks
Due to the prevalence of Wireless Sensor Networks (WSNs) in the many mission-critical applications such as military areas, security has been considered as one of the essential parameters in Quality of Service (QoS), and Intrusion Detection System (IDS) is considered as a fundamental requirement for security in these networks. This paper presents a lightweight Intrusion Detection System to prote...
متن کاملA principled approach to remove false alarms by modelling the context of a face detector
In this article we present a new method to enhance object detection by removing false alarms in a principled way with few parameters. The method models the output of an object classifier which we consider as the context. A hierarchical model is built using the detection distribution around a target sub-window to discriminate between false alarms and true detections. The specific case of face de...
متن کاملA Novel Two-Level Shape Descriptor for Pedestrian Detection
The demand for pedestrian detection and tracking algorithms is rapidly increasing with applications in security systems, human computer interaction and human activity analysis. A pedestrian is a person standing in an upright position. Previous work involves using various types of image descriptors to detect humans. However, the existing approaches, although exhibit low misdetection rate, result...
متن کاملDwarf Frankenstein is still in your memory: tiny code reuse attacks
Code reuse attacks such as return oriented programming and jump oriented programming are the most popular exploitation methods among attackers. A large number of practical and non-practical defenses are proposed that differ in their overhead, the source code requirement, detection rate and implementation dependencies. However, a usual aspect among these methods is consideration of the common be...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004