most citedEfficient 3-D Near-Field MIMO-SAR Imaging for Irregular Scanning Geometries

70 citations · 220 across the 9 of their papers we have counts for

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cs.CV2023

Cutting-Edge Techniques for Depth Map Super-Resolution

Ryan Peterson, Josiah Smith

To overcome hardware limitations in commercially available depth sensors which result in low-resolution depth maps, depth map super-resolution (DMSR) is a practical and valuable co…

cs.CV2023

A Vision Transformer Approach for Efficient Near-Field Irregular SAR Super-Resolution

Josiah Smith, Yusef Alimam, Geetika Vedula +1

In this paper, we develop a novel super-resolution algorithm for near-field synthetic-aperture radar (SAR) under irregular scanning geometries. As fifth-generation (5G) millimeter-…

cs.CV202327 cited

Efficient CNN-based Super Resolution Algorithms for mmWave Mobile Radar Imaging

Christos Vasileiou, Josiah W. Smith, Shiva Thiagarajan +3

In this paper, we introduce an innovative super resolution approach to emerging modes of near-field synthetic aperture radar (SAR) imaging. Recent research extends convolutional ne…

cs.CV202349 cited

Improved Static Hand Gesture Classification on Deep Convolutional Neural Networks using Novel Sterile Training Technique

Josiah Smith, Shiva Thiagarajan, Richard Willis +2

In this paper, we investigate novel data collection and training techniques towards improving classification accuracy of non-moving (static) hand gestures using a convolutional neu…

cs.CV202319 cited

Deep Learning-Based Multiband Signal Fusion for 3-D SAR Super-Resolution

Josiah Smith, Murat Torlak

Three-dimensional (3-D) synthetic aperture radar (SAR) is widely used in many security and industrial applications requiring high-resolution imaging of concealed or occluded object…