Survey of deep learning for high-resolution computer vision


Survey of deep learning for high-resolution computer vision

Efficient High-Resolution Deep Learning: A Survey
arXiv paper abstract
arXiv PDF paper

Cameras in modern devices such as smartphones, satellites and medical equipment are capable of capturing very high resolution images and videos.

… high-resolution data often need to be processed by deep learning models for cancer detection, automated road navigation, weather prediction, surveillance, optimizing agricultural processes and many other applications.

Using high-resolution images and videos as direct inputs for deep learning models creates many challenges due to their high number of parameters, computation cost, inference latency and GPU memory consumption.

Simple approaches such as resizing the images to a lower resolution are common in the literature, however, they typically significantly decrease accuracy.

Several works in the literature propose better alternatives … to deal with the challenges of high-resolution data and improve accuracy and speed while complying with hardware limitations and time restrictions.

This survey describes such efficient high-resolution deep learning methods, summarizes real-world applications … and … information about available high-resolution datasets.

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A computer vision consultant in artificial intelligence and related hitech technologies 37+ years. Am innovator with 66+ patents and ready to help a firm's R&D.