Meta’s new SAM Audio AI model lets users isolate and edit sounds from mixed audio using text, visual or time prompts.

The Temporal Fusion Transformer model provides near-real-time insights into sintering temperatures, addressing critical ...

Deep residual autoencoder for reconstructing and analyzing spectral data using PyTorch. Includes composite loss, UMAP visualization, and spectral diagnostics. Built for unsupervised learning on ...

CNN-Based Models DnCNN Gaussian Noise Denoising Denoising Convolutional Neural Network with residual learning, predicts noise residual instead of clean image, effective for Gaussian noise. DnCNN ...

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...

Residual value is the estimated value of an asset at the end of its useful life. It's used to figure out things like the value of a car at the end of a lease or how much equipment is worth after it's ...

Abstract: Indoor radio maps with frequency domain data are difficult to reconstruct when only limited measurements at a few locations are available. Naive convolutional neural networks suffer from ...

TROY, Mich.: 19 Nov. 2024 — With new- and used-vehicle prices still elevated, budget-conscious shoppers are seeking vehicles that will provide long-term value, highlighting the importance of the J.D.

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...