A Scientific Reports study developed a pattern neural network that integrates total antioxidant status with clinical and ...
Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...
Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
Fulfilment services startup QuickShift has raised INR 22 Cr ($2.5 Mn) in a Pre-Series A round led by Atomic Capital, with participation from Axilor Ventures and a few other unnamed investors. The ...
Mobility startup IntrCity SmartBus has secured INR 250 Cr (about $28.3 Mn) in its Series D funding round, led by A91 Partners. IntrCity cofounder Kapil Raizada told Inc42 that the capital will ...
Broadcast TV continues to draw big audiences. And they are increasingly getting special events, award shows and sports — lots of sports. By John Koblin MTV’s “Video Music Awards” had been a cable-only ...
HOUSTON – (Oct. 14, 2025) – When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is under scrutiny for ...
Abstract: Optimizing the performance of deep neural networks (DNNs) remains a significant challenge due to the sensitivity of models to both hyperparameter selection and weight initialization.
in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...
Abstract: Implicit neural representations (INRs) such as NeRF and SIREN encode a signal in neural network parameters and show excellent results for signal reconstruction. Using INRs for downstream ...
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