Abstract: The present paper investigates the application of TensorFlow Lite to deploy the Convolutional Neural Network on Rasberry Pi for real-time image classification, considering specifically the ...

ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...

Binary cross-entropy (BCE) is the default loss function for binary classification—but it breaks down badly on imbalanced datasets. The reason is subtle but important: BCE weighs mistakes from both ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

Abstract: With an emphasis on convolutional neural networks (CNNs), this research does a thorough analysis of the effectiveness and suitability of the TensorFlow and PyTorch frameworks for image ...

Suggested way to run the project It is suggested to run with docker, using the base image tensorflow/tensorflow:-gpu-jupyter. Adapt the following command: sudo docker ...

It would be nice to know exactly on which versions of pytorch and tensorflow these tutorials were tested. Also, do you use tensorflow ? by looking at the code it does seems so..