Benchmarking CNN Architectures for Tool Classification: Evaluating CNN Performance on a Unique Dataset Generated by Novel Image Acquisition System

Benchmarking CNN Architectures for Tool Classification: Evaluating CNN Performance on a Unique Dataset Generated by Novel Image Acquisition System

In this study, we introduce the ToolSurface-144 dataset, which is presented here for the first time. It comprises four subsets – Full R, Full S, Top R, and Top S – each containing 144 tool classes captured under varying illumination conditions and fields of view. A newly develo...

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Bibliographic Details
Main Authors: Muhenad Bilal, Ranadheer Podishetti, Daniel Grossmann, Markus Bregulla
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Tool classification
machining tools
CNN benchmarking
transfer learning
generalization performance
illumination conditions
Online Access:https://ieeexplore.ieee.org/document/11017576/
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