In deep learning, classification models don’t just need to make predictions—they need to express confidence. That’s where the Softmax activation function comes in. Softmax takes the raw, unbounded ...

Learn how Log Softmax works and how to implement it in Python with this beginner-friendly guide. Understand the concept, see practical examples, and apply it to your deep learning projects.

The identification of wheat infections has always been a considerable problem in agricultural forecasting. This paper presents an automated classification framework for wheat illnesses utilising ...

Introduction: Motor bearing faults seriously affect industrial safety and efficiency. Traditional diagnosis methods often lack adaptability across conditions and rely heavily on labeled data. This ...

Sheldon Shealer is an award-winning sports journalist with more than 30 years of state and national high school sports coverage, which includes creating the Maryland high school football media state ...

Abstract: This study proposes a new self-knowledge distillation method to enhance the classification performance of deep learning models. Compared to traditional knowledge distillation, which relies ...

Recent research has focused on multimodal medical image segmentation. A cascaded V-net and H-DenseUNet approach have improved Dice scores, but at the expense of high computational complexity.

Abstract: Typically, Softmax is used in the final layer of a neural network to get a probability distribution for output classes. But the main problem with Softmax is that it is computationally ...

ABSTRACT: This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional ...

In today's digital landscape, organizations face an unprecedented challenge: managing and protecting ever-growing volumes of data spread across multiple environments. As someone deeply involved in ...