AI river forecasts may be accurate, but based on flawed logic

Artificial intelligence is changing how we predict river flow—but a new study led by researchers at the University of British ...
Ministry of Testing

Back to the basics: Rethinking how we use AI in testing

A simple rule of thumb: In general, AI is best reserved for well-defined, repetitive tasks. This includes anything that ...
IEEE

Comparison of Deep-Learning Models for Classification of Cellular Phenotype From Flow Cytometry Data

Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
Reuters

As data flow revives, Fed still faces a deep policy divide

WASHINGTON, Nov 18 (Reuters) - A divided U.S. Federal Reserve begins receiving updated economic reports from the now-reopened federal government this week as policymakers hope for clarity in their ...
Ars Technica

Gemini Deep Research comes to Google Finance, backed by prediction market data

Google has announced new features in the popular Google Finance platform, and it leans heavily on Google’s tried-and-true strategy of more AI in more places. This builds on Google’s last Finance ...
T&D

Utility Basics: Weather Data in Utility Operations

Utilities monitor surface weather through their own networks and external sources like federal, state, and private stations to fill geographic gaps and improve situational awareness. Aggregation ...
IEEE

A Geometric Deep Learning Approach to Traffic Flow Shockwave Prediction on Freeways Using Vehicle Trajectory Data and HD Map

Abstract: Accurately predicting the occurrence, amplitude, and propagation speed of traffic flow shockwaves are essential for dynamic traffic control to mitigate traffic congestion. However, ...
GitHub

low-level-api-tensorflow

Implementation of multiple deep learning models using Keras Functional API, including a CNN on MNIST, a multi-input/multi-output example, and a toy ResNet on CIFAR-10 ...
GitHub

low-level-api-tensorflow

Practical implementation of image data augmentation using TensorFlow and Keras preprocessing layers. Includes real-time transformations, visual comparisons, and training integration to improve model ...
C&EN

A Deep-Learned Monolithic Nanoparticle Asymmetric Thermal Flow Sensor for Flow Vector Estimation

Wearable Soft Electronics Lab, Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea Institute of Advanced Machinery and Design (SNU-IAMD), Seoul ...