Image Classification Techniques Leveraging Support Vector Machines Decision Trees and Neural Networks
Amit Karbhari Mogal, Vivek Ravishankar Dubey · 2024
This book chapter explores advanced methodologies in image classification through the integration of hybrid models, specifically focusing on the synergistic application of Support Vector Machines (SVM), Decision Trees, and Neural Networks. With the rapid evolution of image processing technologies, the necessity for sophisticated classification techniques has become increasingly critical. The chapter delves into the architectural frameworks of hybrid models, emphasizing the benefits of combining diverse classification algorithms to enhance accuracy and robustness. Furthermore, it addresses the challenges and limitations inherent in hybrid modeling, alongside advanced training and optimization strategies that are vital for effective implementation. A comprehensive examination of performance evaluation metrics provides a benchmark for assessing the efficacy of hybrid models against traditional classifiers, highlighting their superior performance across various applications. The integration of domain knowledge with automated feature selection techniques was also discussed, offering insights into the refinement of model inputs. This chapter serves as a significant contribution to the field, paving the way for future research and practical applications in image classification.