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Template Matching

Template matching is a technique that is used to find a subimage or a patch (called the template) within a larger image. The basic idea behind template matching is to slide the template image over the larger image and compare the template to each portion of the larger image to determine the similarity between the template and the corresponding portion of the larger image.

Papers

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Showing 61–70 of 219 papers

TitleStatusHype
A Neural Template Matching Method to Detect Knee Joint Areas—0
Deep Learning Improves Template Matching by Normalized Cross Correlation—0
Adaptive Template Matching with Shift-Invariant Semi-NMF—0
A 9T4R RRAM-Based ACAM for Analogue Template Matching at the Edge—0
BACTrack: Building Appearance Collection for Aerial Tracking—0
An Edge Map based Ensemble Solution to Detect Water Level in Stream—0
Autonomous Stabilization of Retinal Videos for Streamlining Assessment of Spontaneous Venous Pulsations—0
Autonomous crater detection on asteroids using a fully-convolutional neural network—0
A MAX-AFFINE SPLINE PERSPECTIVE OF RECURRENT NEURAL NETWORKS—0
Active 6D Pose Estimation for Textureless Objects using Multi-View RGB Frames—0
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