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In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model are trained on new data. [1] Fine-tuning can be done on the entire neural network, or on only a subset of its layers, in which case the layers that are not being fine-tuned are "frozen" (i.e., not changed during backpropagation). [2]
Chiffonade [cut] of basil. Chiffonade (French: [ʃi.fɔ.nad]) is a slicing technique in which leafy green vegetables such as spinach, sorrel, or Swiss chard, or a flat-leaved herb like basil, are cut into long, thin strips. [1] This is accomplished by stacking leaves, rolling them tightly, then slicing the leaves perpendicular to the roll. [2]
Self-aligned blocking or cutting is currently being targeted for use with SAQP for sub-30 nm pitches. [88] The lines to be cut are divided into two materials, which can be etched selectively. One cut mask only cuts every other line made of one material, while the other cut mask cuts the remaining lines made of the other material.
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Due to the free forms that naturally occur, the result is often difficult to manufacture. For that reason the result emerging from topology optimization is often fine-tuned for manufacturability. Adding constraints to the formulation in order to increase the manufacturability is an active field of research.
During the cutting process, a fundamental parameter to be considered is the nesting layout, which is the arrangement of the different shapes to be cut from the fabric in order to reduce the scraps. [ citation needed ] The patterns are generally created digitally and, when possible, given to a CNC machine or, otherwise, replicated by hand.
The curls I get from the Airwrap don't really last on my ultra long hair. That, my friends, is where the magic of the Beachwaver comes in. It's incredibly easy to use and creates curls and waves ...
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