… Detection via Classification The most common approach to object detection reduces the …
Consider the problem of detecting instances from one object class of fixed size but varying …

… This paper investigates the scale pest disease diagnostics on mobile devices. We deploy
state-of-the art approaches of CNN object detection models for real-time pest recognition in …

… Object Detector to detect the location of a face in a video frame. The cascade object detector
uses the ViolaJones detection … a trained classification model for detection . By default, the …

… vision tasks such as object classification, counting of objects, and object monitoring. This …
literature review focusing on object detection and discusses the object detection techniques. A …

… • We survey the latest low power object detectors for embedded systems and identify the
potential obstacles of using top-down DNN design flows, which may prevent improved DNN …

… ABSTRACT | Object detection, as of one the most … of object detection and its profound
impact on the entire computer vision field. If we consider today’s object detection technique as a …

… In this paper, we provide a review of deep learning-based object detection frameworks… object
detection architectures along with some modifications and useful tricks to improve detection …

… an image based object recognition and tracking method for mobile AR-devices and the
correlative process to generate the required data. The object recognition and tracking base on …

… power systems for foreign object differentiation and detection. This method overcomes the
… size that plague other foreign object detection and parasitic heating sensing techniques. …

… To further demonstrate the practical usage of MetaOD, we use the synthetic images that
cause erroneous detection results to retrain the model. Our results show that the model …