25 research outputs found
Recommended from our members
Differential heart rate conditioning and lever lift suppression in restrained rabbits
Four rabbits received two adaptation sessions to two tones differing in frequency superimposed on a variable interval 30 sec schedule of water reinforcement. This was followed by eight sessions of differential classical conditioning in which one frequency tone was immediately followed by shock, eight sessions of extinction and 16 sessions of discrimination reversal training. During acquisition training all rabbits showed suppression of the lever lift lick (LLL) response and a heart rate (HR) decrease to the reinforced stimulus. Three animals extinguished on both measures after eight sessions of extinction. Although all rabbits subsequently revealed LLL discrimination reversals, evidence, of HR reversal was clearcut in only one animal. The few within animal differences noted in performance between response systems were not attributable to relative differences or changes in baseline behavior
Learning a Sparse Representation for Object Detection
We present an approach for learning to detect objects in still gray images, that is based on a sparse, part-based representation of objects. A vocabulary of information-rich object parts is automatically constructed from a set of sample images of the object class of interest. Images are then represented using parts from this vocabulary, along with spatial relations observed among them. Based on this representation, a feature-efficient learning algorithm is used to learn to detect instances of the object class. The framework developed can be applied to any object with distinguishable parts in a relatively fixed spatial configuration. We report experiments on images of side views of cars. Our experiments show that the method achieves high detection accuracy on a difficult test set of real-world images, and is highly robust to partial occlusion and background variation. In addition, we discuss and offer solutions to several methodological issues that are significant for the research community to be able to evaluate object detection approaches