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A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
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A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

DOI:
10.3791/60763-v

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05:41 min

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February 06, 2020

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1Department of Neurology,David Geffen School of Medicine, University of California, Los Angeles

Capitoli

  • 00:05Introduction
  • 01:05Tensor Box
  • 02:26YOLOv3 and Openpose
  • 03:37Openpose
  • 03:58Results: Deepbehavior Toolbox
  • 04:41Conclusion

Summary

Traduzione automatica

Traduzione automatica

The purpose of this protocol is to utilize pre-built convolutional neural nets to automate behavior tracking and perform detailed behavior analysis. Behavior tracking can be applied to any video data or sequences of images and is generalizable to track any user-defined object.

Tags

Deep LearningBehavior AnalysisAutomated Behavior QuantificationDeepBehavior ToolboxTensor BoxObject DetectionMulti-object TrackingHuman Pose TrackingMATLABConvolutional Neural NetworkYOLOv3Object LabelingDeep Learning Implementation

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