Sensors for ADAS Technology: 3. RADARs
ADAS sensors: 2. LiDARs
ADAS sensors: 1. RGB cameras
Agricultural yield prediction using Deep Learning
Intrusion Detection with Deep Learning
Detecting physical and virtual intrusions is a key process in ensuring information and property security. Physical intrusion detection refers to all attempts at break-ins to
GAN for non-rigid object tracking
Object identification and tracking remains a challenging task in computer vision, despite advances in hardware, computational, and algorithmic developments. Difficulties arise, in part, due to
Object Tracking at High fps
Object tracking in video sequences is a classical challenge in computer vision, which finds applications in nearly all domains of the industry: from assembly line
High Resolution Image Reconstruction
Recovering a high-resolution (HR) image from a low resolution one is a classical problem in computer vision for which many algorithms have been developed to
Temporal point process sampling in video
Object identification and tracking in a sequence of frames (video) consists of sampling of the scene, by e.g raster or uniform scatter, to extract features
RGB-D SLAM building 3D models from depth cameras
In the past few years, depth cameras became common and easy to get. Several product are available in the market at a reasonable price, e.g.
Sensors for ADAS Technology: 3. RADARs
ADAS sensors: 2. LiDARs
ADAS sensors: 1. RGB cameras
Agricultural yield prediction using Deep Learning
Intrusion Detection with Deep Learning
Detecting physical and virtual intrusions is a key process in ensuring information and property security. Physical intrusion detection refers to all attempts at break-ins to
GAN for non-rigid object tracking
Object identification and tracking remains a challenging task in computer vision, despite advances in hardware, computational, and algorithmic developments. Difficulties arise, in part, due to
Object Tracking at High fps
Object tracking in video sequences is a classical challenge in computer vision, which finds applications in nearly all domains of the industry: from assembly line
High Resolution Image Reconstruction
Recovering a high-resolution (HR) image from a low resolution one is a classical problem in computer vision for which many algorithms have been developed to
Temporal point process sampling in video
Object identification and tracking in a sequence of frames (video) consists of sampling of the scene, by e.g raster or uniform scatter, to extract features
RGB-D SLAM building 3D models from depth cameras
In the past few years, depth cameras became common and easy to get. Several product are available in the market at a reasonable price, e.g.
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