This project focuses on the task of binary image classification using custom implementations of various deep learning models with PyTorch. The models used in this project include variants of VGG, ...

VGG16 was developed at the University of Stanford. We will use this pre trained model and add dense layer of logistic regression at the end for binary classification of images. The only part of the ...

Binary Neural Networks present an opportunity for developing Neural Networks that require less computing power as well as energy. This is done through the use of binary values for weights and inputs.

The Neural Network Architecture In a previous article in this series, I described how to design and implement a neural network for binary classification using the Banknote Authentication data. One ...

Robust Multi-Classifier for Camera Model Identification Based on Convolution Neural Network Abstract: With the prevalence of adopting data-driven convolution neural network (CNN)-based algorithms into ...

Binary classifiers that accept as input an image, ... Facebook’s failure to identify the New Zealand video reminds us that the point-and-click binary classifier model that has become the go-to ...