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The two time-scale update rule (TTUR) is proposed to make GAN convergence more stable by making the learning rate of the generator lower than that of the discriminator. The authors argued that the generator should move slower than the discriminator, so that it does not "drive the discriminator steadily into new regions without capturing its ...
The original GAN method is based on the GAN game, a zero-sum game with 2 players: generator and discriminator. The game is defined over a probability space (,,), The generator's strategy set is the set of all probability measures on (,), and the discriminator's strategy set is the set of measurable functions : [,].
Gallium nitride (Ga N) is a binary III/V direct bandgap semiconductor commonly used in blue light-emitting diodes since the 1990s. The compound is a very hard material that has a Wurtzite crystal structure.
Instead, a catalyst- free high temperature process is used, which requires certain conditions. One of these conditions was high heat. The nanotube growth for c-GaN nanotubes was done at around 1600 degrees Celsius (200 degrees higher than the conditions required to grow h- GaN nanotubes), and was continuously increased throughout the process.
InGaN blue LED (380–405 nm) Spectrum of a white-light LED where GaN or InGaN blue source pumps Ce:YAG phosphor. Indium gallium nitride (InGaN, In x Ga 1−x N) is a semiconductor material made of a mix of gallium nitride (GaN) and indium nitride (InN). It is a ternary group III/group V direct bandgap semiconductor.
Hypothetical, experiments, diffusion, early uses [72] Improved thermal insulation (for pipelines, aerospace, etc.), as well as insulative "glass" if it can be made clear Amorphous metal: Experiments, use in amorphous metal transformers: Armor, implants Bioplastic: Limited commercialization (e.g. polylactic acid in 3D printing)
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The Fréchet inception distance (FID) is a metric used to assess the quality of images created by a generative model, like a generative adversarial network (GAN) [1] or a diffusion model. [2] [3] The FID compares the distribution of generated images with the distribution of a set of real images (a "ground truth" set).