Category Physics

T2CI GAN: A Deep Learning Model that Generates Compressed Images from Text

T2CI GAN: A deep learning model that generates compressed images from text
The significance of applying the simple transformation on JPEG Compressed DCT images. Credit: Rajesh et al.

Generative adversarial networks (GANs), a class of machine learning frameworks that can generate new texts, images, videos, and voice recordings, have been found to be highly valuable for tackling numerous real-world problems. For instance, GANs have been successfully used to generate image datasets to train other deep learning algorithms, to generate videos or animations for specific uses, and to create suitable captions for images.

Researchers at the Computer Vision and Biometrics Lab of IIT Allahabad and Vignan University in India have recently developed a new GAN-based model that can generate compressed images from text-based descriptions...

Read More

The Next Wonder Semiconductor

scanning ultrafast electron microscope
The scanning ultrafast electron microscope (SUEM) couples a femtosecond pulsed laser with a scanning electron microscope, which enables time-resolved imaging of microscopic energy transport processes with simultaneously high spatial and temporal resolutions
Photo Credit: 
MATT PERKO

With scanning ultrafast electron microscopy, researchers unveil promising hot photocarrier transport properties of cubic boron arsenide. In a study that confirms its promise as the next-generation semiconductor material, UC Santa Barbara researchers have directly visualized the photocarrier transport properties of cubic boron arsenide single crystals.

“We were able to visualize how the charge moves in our sample,” said Bolin Liao, an assistant professor of mechanical engineering in the College of Engineeri...

Read More

Improving Light Absorption in Perovskite/Si Tandem Solar Cells

1. (a) A schematic of the PDMS layer containing SGA phosphors and SiO2 nanoparticles, (b) photographs of the PDMS layer with SGA phosphors and SiO2 nanoparticles under ambient light and UV light (λ = 365 nm), (c) a schematic of perovskite/Si tandem solar cell with the PDMS layer containing SGA phosphors and SiO2 nanoparticles, and (d) a cross-sectional SEM image of the perovskite–Si solar cell.

A research team, affiliated with UNIST has succeeded in achieving a power conversion efficiency (PEC) of 23.50% in a perovskite-silicon tandem solar cell built with a special textured anti-reflective coating (ARC) polymeric film. According to the research team, the PCE of the device with the ARC film was sustained for 120 hours, maintaining 91% of its initial value.

This breakthrough has b...

Read More

New Computing Architecture: Deep Learning with Light

Artist’s rendering of a smart transceiver. The dark blue device has golden pathways and rectangles, which represent the wires that connect the smart transceiver chip to a circuit board. A light blue square covered with thin lines rises from the middle, to represent the smart transceiver chip. The thin lines represent an array of fibers that move light from lasers in and out of the chip.
Caption:This rendering shows a novel piece of hardware, called a smart transceiver, that uses technology known as silicon photonics to dramatically accelerate one of the most memory-intensive steps of running a machine-learning model. This can enable an edge device, like a smart home speaker, to perform computations with more than a hundred-fold improvement in energy efficiency.
Credits:Image: Alex Sludds. Edited by MIT New

A new method uses optics to accelerate machine-learning computations on smart speakers and other low-power connected devices. The technique may enable self-driving cars to make decisions in realtime while only using a fraction of the energy that is currently demanded by their power-hungry on-board computers.

Ask a smart home device for the weather forecast, and it...

Read More