Computer and Machine Vision: Theory, Algorithms, Practicalities

By E. R. Davies. 2012

302 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

State of the Art in Defect Detection Based on Machine Vision (2021, unknown): “Machine vision is one of the key technologies used to perform intelligent manufacturing, and it has become an effective way to replace artificial visual inspection [13, 14].”
Smart logistics based on the internet of things technology: an overview (2020, background): “For example, machine vision (Davies 2012) makes robots collect more realtime data and undertakes more efficient and precise identification and detection.”
HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient (2017, methodology): “This filter is fast to compute and is effective for smoothing rectangular shapes (Davies 2012) like domain structures in Hi-C data.”
Feature selection for surface defect classification of extruded aluminum profiles (2016, background): “The typical components of a machine vision system include [3]:”
Assessment of Convolutional Neural Networks for Automated Classification of Chest Radiographs. (2019, methodology): “14) for contrast enhancement (17), downsampling to a standard 224 3 224 input resolution to enable use of standard CNN architectures with pretrained weights (torchsample, version 0.”