Recognizing highly occluded objects is believed to arise from the interaction between the brain's vision and cognition-controlling areas, although supporting neuroimaging data are currently limited.
Sep 29, 2023
An effective approach in recognizing occluded objects which are partially blocked from sight is to detect a number of essential features on the boundary of ...
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Feb 2, 2024 · simple cheap trick is to train the model to detect the center of an object, then draw a box around it, based on box positions, size and overlap ...
Feature interactions may be the key to recognize occluded objects. In this paper, we propose a framework to integrate local feature interactions in terms of ...
Oct 27, 2023 · Abstract:Recognizing multiple objects in an image is challenging due to occlusions, and becomes even more so when the objects are small.
Oct 4, 2016 · We argue that the computational mechanisms subserving recognition of heavily occluded objects rely on neural circuits with recurrent ...
Detecting partially occluded objects is a difficult task. Our experimental results show that deep learning ap- proaches, such as Faster R-CNN, ...
We have proposed a method to recognize partially occluded three-dimensional (3D) objects by using 3D volumetric reconstruction integral imaging (II). An II ...
In this paper we apply clustering methods to a new problem domain and present a new method based on a cluster-structure paradigm for the recognition of 2-D ...
Pattern recognition from sparse information is essential when objects are rendered under poor illumination or when they are significantly occluded. Here we ...