Cost-Effective Object Detection: Active Sample Mining With Switchable Selection Criteria
نویسندگان
چکیده
منابع مشابه
Object Detection with Active Sample Harvesting
The work presented in this dissertation lies in the domains of image classification, object detection, and machine learning. Whether it is training image classifiers or object detectors, the learning phase consists in finding an optimal boundary between populations of samples. In practice, all the samples are not equally important: some examples are trivially classified and do not bring much to...
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Object detectors based on the sliding window technique are usually trained in two successive steps: first, an initial classifier is trained on a population of positive samples (i.e. images of the object to detect) and negative samples randomly extracted from scenes which do not contain the object to detect. Then, the scenes are scanned with that initial classifier to enrich the initial set with...
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Object detection is the automatic determination of image locations at which instances of a predefined object class are present. Numerous methods for object detection exist (e.g., (Viola and Jones, 2001; Fergus et al., 2006)), most of which scan a part of the image at some stage of the object-detection process. Until now, this scanning is performed in a passive manner: local image samples extrac...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Networks and Learning Systems
سال: 2019
ISSN: 2162-237X,2162-2388
DOI: 10.1109/tnnls.2018.2852783