In a past university project my teammates and I were researching which parts of a face are the most discriminative for a convolutional neural network to classify emotions. For that we trained several facial emotion recognition models with TensorFlow on two databases: FER+ and RAF-DB. The final model architecture as…
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This project was done for the Mobile Robotics course in the Intelligent Interactive Systems master’s program at Pompeu Fabra University, Barcelona. In the following I will give a short overview of how I approached the task of implementing a localization module and present the results. The code for this project…
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When training an object detection model, you have surely stumbled across the Intersection over Union, in short IoU. In this short post, I will explain what it is and how to implement it in native Python. Furthermore, I will describe the implementation in Tensorflow using vector operations, so that it…
Comments closedSimple object localization and classification using a convolutional neural network build with Tensorflow/Keras in Python. In my previous post I wrote about a simple object localization problem: predicting the bounding box of a single rectangle on neutral background. However, this approach was limited to a single shape and could not…
Comments closedSimple introduction to object localization using a convolutional neural network build with Tensorflow/Keras in Python. In the past days I worked myself into object detection with neural networks. For simplicity, I decided to start with a simple task: predict the bounding box of one single rectangle on a neutral background.…
Comments closedIncluding feature selection methods as a preprocessing step in predictive modeling comes with several advantages. It can reduce model complexity, enhance learning efficiency, and can even increase predictive power by reducing noise. In this blog post I want to introduce a simple python implementation of the correlation-based feature selection algorithm…
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