Deep Learning for Multimedia Processing Applications

CHAPTER 13 From Data Quality to Model Performance Navigating the Landscape of Deep Learning Model Evaluation

Muhammad Akram, Wajid Hassan Moosa, and Najiba

Faculty of Information and Communication Technology, Balochistan University of Information Technology, Engineering and Management Sciences, Quetta, Pakistan

DOI: 10.1201/9781032646268-13

13.1 Introduction

The development and evaluation of deep learning models rely heavily on the quality and diversity of the data sets used to train them. Benchmarks are crucial for evaluating the performance of these models, while validations ensure that they are performing as intended. The importance of these topics cannot be overstated, as they are essential for the successful application of deep learning ...