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Model Card for Model ID

Classification of lego technic pieces under basic room lighting conditions

Model Details

Model Description

CNN designed without using a pre-trained model to classify images of lego pieces into 7 categories. Achieved a 93% validation accuracy

  • Developed by: Aveek Goswami, Amos Koh
  • Funded by [optional]: Nullspace Robotics Singapore
  • Model type: Convolutional Neural Network

Model Sources [optional]

Uses

Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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Model Card Contact

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