AI optimists envision a future where artificial general intelligence (AGI) surpasses human intelligence, but the path remains riddled with scientific and logistical hurdles.
A researcher, professor and federal policy adviser, he guided students who went on to do groundbreaking work in connecting ...
Abstract: Existing airborne laser scanning (ALS) point cloud semantic segmentation approaches are limited by their overreliances on sufficient point-wise annotations that further confine their ...
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Abstract: We propose a generative adversarial network for point cloud upsampling, which can not only make the upsampled points evenly distributed on the underlying surface but also efficiently ...
Abstract: Point cloud completion concerns the inference of the completed geometries for real-scanned point clouds that are sparse and incomplete due to occlusion, noise, and viewpoint. Previous ...
Abstract: At present, with the original point cloud as input, most of the object detectors use Pointnet++ to extract features of the point cloud based on the Farthest Point Sampling (FPS). However, ...
With this acquisition, Net at Work significantly expands its Midwestern US footprint As part of the acquisition, Net at Work purchased Nterfuse, a specialized software platform NCS was founded in 1996 ...
Abstract: Affective brain–computer interfaces (aBCIs) are an emerging technology that decodes brain signals—primarily electroencephalography (EEG)—to monitor and regulate emotional states in real time ...
There are few certainties in life: death, taxes and massively increased workloads on infrastructures through the unstoppable rise of AI. And enterprises and connectivity providers know only too well ...
Abstract: We present CO-Net++, a cohesive framework that optimizes multiple point cloud tasks collectively across heterogeneous dataset domains with a two-stage feature rectification strategy. The ...
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