Sentence examples for both computer vision and from inspiring English sources

Introduction of RGB-D sensors together with the efforts on open-source point-cloud processing tools boosted research in both computer vision and robotics.

Subspace and similarity metric learning are important issues for image and video analysis in the scenarios of both computer vision and multimedia fields.

Such a task is particularly challenging considering that we must find a semantic correspondence between captions and the respective image, a challenge for both computer vision and natural language processing areas.

This research encompasses problems in both computer vision and computer graphics, including structure from motion, multi-view stereo, graph algorithms for analyzing large image collections, image-based rendering, and 3D navigation interfaces.

ML can be used in both computer vision and image processing.

Within this framework, action analysis is a highly challenging issue that involves both computer vision and machine learning methodologies.

Surface matching is a well researched topic in both Computer Vision (CV) and terrestrial laser scanning (TLS) or ground based light detection and ranging (LiDAR), but the extent of the range images derived from these technologies is typically orders of magnitude smaller than those derived from airborne laser scanning (ALS), also known as airborne LiDAR.

Indeed, recent advances of both computer vision algorithms and computer processing power now allow the study of the spatio-temporal wave field with unprecedented accuracy, especially at small scales.

Visual Question Answering (VQA) is a challenging task that has received increasing attention from both the computer vision and the natural language processing communities.

There are many potential future applications of this type of analysis, both within computer vision and in other domains.

His research interests include computer vision and computational photography.