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Grayscale image colorization methods: Overview and evaluation
Colorization is a process of converting grayscale images into visually acceptable color
images. The main goal is to convince the viewer of the authenticity of the result. Grayscale …
images. The main goal is to convince the viewer of the authenticity of the result. Grayscale …
Applications and challenges of artificial intelligence in space missions
PA Oche, GA Ewa, N Ibekwe - IEEE Access, 2021 - ieeexplore.ieee.org
Artificial Intelligence (AI) is increasingly finding acceptance in the space community,
especially Machine Learning (ML), a subdomain of AI. ML algorithms now find numerous …
especially Machine Learning (ML), a subdomain of AI. ML algorithms now find numerous …
TUM-ParticleTyper: A detection and quantification tool for automated analysis of (Microplastic) particles and fibers
E Von Der Esch, AJ Kohles, PM Anger, R Hoppe… - PLoS …, 2020 - journals.plos.org
TUM-ParticleTyper is a novel program for the automated detection, quantification and
morphological characterization of fragments, including particles and fibers, in images from …
morphological characterization of fragments, including particles and fibers, in images from …
Implementation of an open source algorithm for particle recognition and morphological characterisation for microplastic analysis by means of Raman …
PM Anger, L Prechtl, M Elsner, R Niessner… - Analytical …, 2019 - pubs.rsc.org
Microplastic (MP, ie synthetic polymer particles of 1 μm–5 mm) is not only a suspected
environmental contaminant, but also a challenging target for chemical analysis. To analyse …
environmental contaminant, but also a challenging target for chemical analysis. To analyse …
Segmentation performance evaluation for object-based remotely sensed image analysis
The initial step in most object-based classification methodologies is the application of a
segmentation algorithm to define objects. Modelling the human visual process of object …
segmentation algorithm to define objects. Modelling the human visual process of object …
Performance characterization in computer vision: A guide to best practices
It is frequently remarked that designers of computer vision algorithms and systems cannot
reliably predict how algorithms will respond to new problems. A variety of reasons have …
reliably predict how algorithms will respond to new problems. A variety of reasons have …
Automated advanced image processing for micromodel flow experiments; an application using labVIEW
The study of multi-phase fluid flow in microfluidic devices provides an opportunity for
researchers to observe fluid transport mechanisms and characterize influencing factors …
researchers to observe fluid transport mechanisms and characterize influencing factors …
Performance measures for object detection evaluation
We propose a new procedure for quantitative evaluation of object detection algorithms. The
procedure consists of a matching stage for finding correspondences between reference and …
procedure consists of a matching stage for finding correspondences between reference and …
[PDF][PDF] Performance evaluation by image processing techniques in archery–a case study
S Debnath, S Debnath - Int J New Technol Sci Eng, 2016 - researchgate.net
Archers find postural sway, unforced changes and irregular displacement that negatively
correlate to their technical level and hence their performance. Using image processing, the …
correlate to their technical level and hence their performance. Using image processing, the …
Performance benchmark of DSP and FPGA implementations of low-level vision algorithms
D Baumgartner, P Rossler… - 2007 IEEE Conference …, 2007 - ieeexplore.ieee.org
Selecting an embedded hardware platform for image processing has a big influence on the
achievable performance. This paper reports our work on a performance benchmark of …
achievable performance. This paper reports our work on a performance benchmark of …