Deep learning reveals nanoparticle shape from routine tracking analysis without new hardware

Researchers at the University of Tokyo and the Innovation Center of NanoMedicine (iCONM) have developed an artificial ...
AlphaGalileo

Transfer learning boosts leaf trait estimation from space

Leaf functional traits—chlorophyll (CHL), carotenoid (CAR), equivalent water thickness (EWT), nitrogen (N), and leaf mass per ...
Microsoft

Probing the Limit of Heat Transfer in Inorganic Crystals with Deep Learning

Heat transfer is a fundamental property of matter. Research spanning decades has attempted to discover materials with exceptional thermal conductivity, yet the upper limit remains unknown. Using deep ...
IEEE

Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016

Abstract: The traditional deep learning-based bearing fault diagnosis approaches assume that the training and test data follow the same distribution. This assumption, however, is not always true for ...
VentureBeat

Building voice AI that listens to everyone: Transfer learning and synthetic speech in action

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Have you ever thought about what it is like ...
C&EN

Transfer-Learning Deep Raman Models Using Semiempirical Quantum Chemistry

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Biophotonic technologies such as Raman spectroscopy are powerful tools for obtaining ...
Scientific Research Publishing

Wu, D., Wang, X. and Wu, S. (2022) Jointly Modeling Transfer Learning of Industrial Chain Information and Deep Learning for Stock Prediction. Expert Systems with Applications ...

ABSTRACT: The forecasting research literature has developed greatly in recent years as a result of advances in information technology. Financial time-series tasks have made substantial use of machine ...
GitHub

Deep learning seismic facies on state-of-the-art CNN architectures

We explore propagation of seismic interpretation by deep learning in stacked 2D sections. We show the application of state-of-the-art image classification algorithms on seismic data. These algorithms ...