IEEE

Continual Learning for Object Classification: Integrating AutoML for Binary Classification Tasks Within a Modular Dynamic Architecture

Abstract: For humans it is quite easy to identify a new object after learning to identify existing ones, but not for a machine. Deep neural networks (DNN) are the foundation of the current ...
Learn With Jay on MSN

Activation functions in neural networks: Types and examples

In this video, we will see What is Activation Function in Neural network, types of Activation function in Neural Network, why ...
IEEE

Binary Similarity Few-Shot Object Detection With Modeling of Hard Negative Samples

Abstract: For few-shot object detection, this work proposes a binary similarity detector (BSDet), which realizes a novel similarity-based multiple binary classification and enhances the feature margin ...
Visual Studio Magazine

AdaBoost Binary Classification Using C#

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 ...
The New York Times

Paris Paralympics 2024: How the classification system works

PR1, W1, T51, F58, SL4, KL3, SM11. This is not a test to crack a code. But you will see a series of letter and number combinations while engaging with the Paralympics in Paris. At the Olympics, there ...
Analytics India Magazine

One vs One, One vs Rest with SVM for multi-class classification

Generally, we see the usage of algorithms like SVM and logistic regression in binary classification problems in which using these algorithms we are required to predict one class out of two for any ...
Visual Studio Magazine

Binary Classification Using PyTorch: Training

Dr. James McCaffrey of Microsoft Research continues his examination of creating a PyTorch neural network binary classifier through six steps, here addressing step No. 4: training the network. The goal ...