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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 151–175 of 219 papers

TitleStatusHype
BOP: Benchmark for 6D Object Pose EstimationCode1
Fast and Robust Matching for Multimodal Remote Sensing Image Registration—0
ASR-free CNN-DTW keyword spotting using multilingual bottleneck features for almost zero-resource languages—0
Mammography Dual View Mass Correspondence—0
Fast ASR-free and almost zero-resource keyword spotting using DTW and CNNs for humanitarian monitoring—0
Real-time Lane Marker Detection Using Template Matching with RGB-D Camera—0
TernausNetV2: Fully Convolutional Network for Instance SegmentationCode0
Matching Pixels Using Co-Occurrence Statistics—0
Estimating Carotid Pulse and Breathing Rate from Near-infrared Video of the Neck—0
Design Identification of Curve Patterns on Cultural Heritage Objects: Combining Template Matching and CNN-based Re-Ranking—0
Image-derived generative modeling of pseudo-macromolecular structures - towards the statistical assessment of Electron CryoTomography template matching—0
Secure Face Matching Using Fully Homomorphic EncryptionCode0
Latent Fingerprint Recognition: Role of Texture TemplateCode0
OATM: Occlusion Aware Template Matching by Consensus Set Maximization—0
Learning Dynamic Memory Networks for Object TrackingCode0
APPLE Picker: Automatic Particle Picking, a Low-Effort Cryo-EM FrameworkCode0
Learning Deep Features for One-Class ClassificationCode0
Facial emotion recognition using min-max similarity classifier—0
How deep learning works --The geometry of deep learning—0
MR fingerprinting Deep RecOnstruction NEtwork (DRONE)—0
Real-Time Monocular Pose Estimation of 3D Objects Using Temporally Consistent Local Color Histograms—0
When 3D-Aided 2D Face Recognition Meets Deep Learning: An extended UR2D for Pose-Invariant Face Recognition—0
Fast Screening Algorithm for Rotation and Scale Invariant Template Matching—0
Deep Learning Improves Template Matching by Normalized Cross Correlation—0
View-Invariant Template Matching Using Homography Constraints—0
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