New Diffusion Models Offer Keys To Success For Resource-Scarce Systems
All over the AI field, teams are unlocking new functionality by changing the ways that the models work. Some of this has to ...
AZoOptics2d
In-Line CT Delivers Real-Time Quality Feedback On the Production Line
The moving assembly line has certainly proven its worth over the 100-plus years since Henry Ford introduced the industrial ...
Single-cell method enables rapid identification of airborne pathogens in real-world environment
Aerosols play a critical role in the transmission of airborne pathogens by acting as carriers that transport pathogens ...
Scientific Research Publishing4d
A Conceptual Model for Improving Perovskite Solar Cells Efficiency Using Machine Learning ()
Binjumah, W. (2025) A Conceptual Model for Improving Perovskite Solar Cells Efficiency Using Machine Learning. International ...
As technology evolves, it becomes harder to tell ‘real’ AI from marketing
In his college courses at Stanford University, Jehangir Amjad poses a curious question to his students: Was the 1969 moon ...
Psychology Today6d
State-of-the-Art AI Predicts Gene Activity in Human Cells
An AI foundation model capable of predicting gene activity across many different human cell types may expedite research for ...
GlobalSpec7d
Doubling-down on algorithms improves drone detection, tracking
Additionally, tracker reliability allows the system to dynamically adapt to changes in the tracking environment. For instance ...
AZoBuild8d
Application of Deep Learning in Construction Engineering and Management
Analyzing 296 deep learning studies, this review highlights transformative applications in Construction Engineering and ...
openaccessgovernment8d
How AI algorithms can revolutionise medical imaging for cancer detection
AI is beginning to find its place within the healthcare sector, particularly in medical imaging and tumour detection ...
GitHub14d
A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing
I. Rahmati, H. Shahmansouri, and A. Movaghar, "QECO: A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing". @article{rahmati2024qeco, ...