Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, ...
Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...
WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
In the rapidly evolving artificial intelligence landscape, one of the most persistent challenges has been the resource-intensive process of optimizing neural networks for deployment. While AI tools ...
When it comes to neural network machine learning — recently popularized by artificial intelligence (AI) applications — a team of Bucknell University analytics researchers have found that less may be ...
A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...
Deep Learning with Yacine on MSN
RMSProp optimization from scratch in Python
Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks ...
VFF-Net introduces three new methodologies: label-wise noise labelling (LWNL), cosine similarity-based contrastive loss (CSCL), and layer grouping (LG), addressing the challenges of applying a forward ...
MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback