Automated Muzzle Detection and Biometric Identification via Few-Shot Deep Transfer Learning of Mixed Breed Cattle
Livestock welfare and management could be greatly enhanced by the replacement of branding or ear tagging with less invasive visual biometric identification methods. Biometric identification of cattle from muzzle patterns has previously indicated promising results. Significant barriers exist in the t...
Saved in:
Main Authors: | Ali Shojaeipour, Greg Falzon, Paul Kwan, Nooshin Hadavi, Frances C. Cowley, David Paul |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/684cef23a2854930b488e49da43bfc5c |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Few-Shot Object Detection via Sample Processing
by: Honghui Xu, et al.
Published: (2021) -
Meta-Seg: A Generalized Meta-Learning Framework for Multi-Class Few-Shot Semantic Segmentation
by: Zhiying Cao, et al.
Published: (2019) -
Optimizing Few-Shot Learning Based on Variational Autoencoders
by: Ruoqi Wei, et al.
Published: (2021) -
Task-Adaptive Embedding Learning with Dynamic Kernel Fusion for Few-Shot Remote Sensing Scene Classification
by: Pei Zhang, et al.
Published: (2021) -
Task-Aware Dual Prototypical Network for Few-Shot Human-Object Interaction Recognition
by: AN Ping, JI Zhong, LIU Xiyao
Published: (2021)