NETRA: a hierarchical and partitionable architecture for computer vision systems

NETRA: A Hierarchical and Partitionable Architecture for Computer Vision Systems

Computer vision is regarded as one of the most complex and computationally intensive problems. In general, a Computer Vision System (CVS) attempts to relate scene(s) in terms of model(s). A typical CVS employs algorithms from a very broad spectrum such as such as numerical, image processing, graph algorithms, symbolic processing, and artificial intelligence. This paper presents a multiprocessor...

An Adaptive Architecture for Hierarchical Vision Systems

We describe a machine learning architecture for hierarchical vision systems. These vision systems work by successively grouping visual constructs at one level, selecting the most promising, and passing them up to higher levels of processing. This continues from the pixel-level of the image to the object-model evel. Traditionally, researchers have used static heuristics at each level to select t...

Design of a Machine Learning Architecture for Hierarchical Vision Systems

In this report, we describe a machine learning architecture for hierarchical vision systems. These vision systems work by successively grouping visual constructs at one level, selecting the most promising, and passing them up to higher levels of processing. This continues from the pixel-level of the image to the object-model level. Traditionally, researchers have used static heuristics at each ...

Sun Netra T5220 Server Architecture

Computer assisted instruction during quarantine and computer vision syndrome

Computer vision syndrome (CVS) is a set of visual, ocular, and musculoskeletal symptoms that result from long-term computer use. These symptoms include eyestrain, dry eyes, burning, pain, redness, blurred vision, etc, which increase with the duration of computer use. Currently, with the closure of schools and universities due to the continued COVID19 pandemic many universities have taken the pr...