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Visual and inertial sensing are two sensory modalities that can be explored to give robust solutions on image segmentation and recovery of 3D structure from images, increasing the capabilities of autonomous vehicles and enlarging the application potential of vision systems.
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The research described in this paper aims to examine and demonstrate the potential of vision-based sensing solutions to meet this requirement.
Here, we take a closer look at the potential role of vision; Specifically, we question the impact that our increasing exposure to images of desirable foods (what is often labelled 'food porn', or 'gastroporn') via digital interfaces might be having, and ask whether it might not inadvertently be exacerbating our desire for food (what we call 'visual hunger').
Long-term complications of diabetes include retinopathy with potential loss of vision; nephropathy leading to renal failure; peripheral neuropathy with risk of foot ulcers, amputations, and Charcot joints; and autonomic neuropathy causing gastrointestinal, genitourinary, and cardiovascular symptoms and sexual dysfunction.
My addiction is to the potential of the vision.
We demonstrate with experimental evidence the potential of computer vision (CV) methods for cranial sex estimation.
The main objective of this paper is to demonstrate the potential of computer vision methods for sex determination from human skull.
We will continue to tap the potential of computer vision in applications that range from simple photo organization to complex video and mobile applications.
Prior to describing the forensic method, it is worth emphasizing that the objective of this paper is to demonstrate the potential of computer vision methods for sex determination from human skull.
This study has shown the potential of machine vision systems to detect cherry tree branches in full foliage season, which is highly promising for the development of automated sweet cherry harvesting systems.
Tech platforms have also recently started paying more attention to visual search too, spying potential to combine the vast quantity of visual data they hold with recent developments in deep learning/AI technology that is helping realize the potential of computer vision.
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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