Deep Learning for Object Recognition in picking tasks

It is divided into the following sections: an introduction of object detection and association tasks, the study of the Person Re-identication Benchmark [2], the dierent

"Builiding correlation strategies for object detection in blurred scenes", in Optoelectronic information processing. VanderLugt, "Signal detection by complex

We find works using synthetic data for object detection/recognition [62, 110, 111, 172], object viewpoint recognition [139], re-identification [14], and human pose estimation

Finally, we adapt also the detection proposal to deal with specific problems of object recognition in different areas. On the one hand, we present a new fully automatic computer

● Herwig (2001, ApJ, 554, L71) and Lawlor & MacDonald (2003, ApJ, 583, 913) assume that the efficiency of the hydrogen ingestion is reduced by buoyancy effects, causing

The client’s model of object life cycle is based on factories and target objects supporting the LifeCycleObject interface. Factories are objects that create other

 using series of many (dozens) of images, in the search of unknown objects moving in any direction and with any proper motion. Track

Foreground segmentation. This module does the foreground object extraction task. Foreground extraction is performed using an approach similar to the one of the semantic