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A lot of efforts have been made to understand visual concepts in still image tasks, e.g., image classification and object detection.
Using a genetic search algorithm for energy efficiency/constrained image tasks, MELOADES satisfied 94% of all task constraints, evaluated only 1.6% of the configuration space, and used 98.5% less energy than an exhaustive search.
More and more sophisticated bioimage analysis tasks need tools to perform heavy duty image tasks such as 3D registration of animals' brains, 3D automatic neuron tracing, etc.
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That is why, recently, the Society of Nuclear Medicine and Molecular Imaging and the Alzheimer's Association have jointly convened the Amyloid Imaging Task Force (AIT) and published the Appropriate Use Criteria for amyloid-PET [ 132, 133].
This project applied Jorgensen's three image retrieval tasks (1995) and Enser's four models of image retrieval (1995) to investigate end-users' image retrieval tasks and image query modes in the field of art history.
Topology is an important prior in many image segmentation tasks.
Geometric moments are used in numerous image analysis tasks.
The story is not different for image restoration tasks.
Graphics processing units let developers run a ton of image processing tasks in parallel.
Deep residual networks have reached the state of the art in many image processing tasks such image classification.
The SAVI Analysis Engine distributes signal and image processing tasks to a Linux cluster where computation is performed.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com