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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A method to visualize internal representations of a convolutional neural network and perform object localization without bounding box annotations. For a university project we investigated the question of where a deep convolutional neural network (CNN) looks, when classifying emotions. For this purpose, we evaluated three visualization methods for CNNs, one…
Comments closedThis 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 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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