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cybertyche commented Dec 13, 2018

Implement progressive versions of hopping and tumbling windows:

  • Both window macro methods should get added versions that take an additional parameter
  • The parameter should represent the time interval that should be used to produce intermediate results of aggregations
  • The parameter should be a clean divisor of the tumble size for tumbling windows and the hop size for hopping windows

This repo contains an implementation code for the weakly supervised surgical tool tracker. In this research, the temporal dependency in surgical video data is modeled using a convolutional LSTM which is trained only on image level labels to detect, localize and track surgical instruments.

  • Updated Sep 1, 2020
  • Python
EdgarACarneiro commented Mar 16, 2021

The current implementation does not allow the overriding of the FlatInterval.equals method since internally some FlatInterval objects are created to optimise data handling. As such, if one does override the equals method with the new properties, the search method brakes.

Possible solutions:

  • Stop creating FlatInterval objects inside the I2BplusTree and just use/ move around the va

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