Genetic programming (GP) has been applied to various binary image classification tasks and achieved promising results. However, existing approaches are difficult to be applied to large binary ...

SVM is a machine learning algorithm used to address binary classification problems (Zhang et al., 2013). It maps the original vectors into a higher-dimensional space and constructs a hyperplane with ...

Neural architectures have accelerated the advancement in various domains by enabling automatic pattern detection, image classification, audio recognition, and face recognition etc. However, they are ...

In [22], the authors proposed a binary classification framework for detecting diabetic retinopathy using transfer learning. They integrate Pyspark with deep learning, leveraging it as a Big Data tool ...

Dr. James McCaffrey from Microsoft Research presents a C# program that illustrates using the AdaBoost algorithm to perform binary classification for spam detection. Compared to other classification ...

This project aims to detect malaria using deep learning techniques. To address this issue, we focus on implementing a supervised learning approach. For model training, we utilize the "Malaria" dataset ...

In this research, we present a Python implementation using TensorFlow to employ the (ViT) model for image classification. Four categories of animals such as (cow, dog, horse and sheep) images will be ...

Image Classification with Convolutional Neural Networks in TensorFlow: Fashion Item Classifier At TrendSetter, our ambition is to consistently remain at the forefront of the fashion e-commerce ...