Deep learning framework for energy consumption forecasting and anomaly detection using a Dual Attention Encoder-Decoder architecture with an interactive analytics dashboard. - SVNSAIRAVIKIRAN/DAEIN ...

Generative AI’s current trajectory relies heavily on Latent Diffusion Models (LDMs) to manage the computational cost of high-resolution synthesis. By compressing data into a lower-dimensional latent ...

Abstract: Reliable and timely data collection poses a significant challenge for underwater wireless sensor networks (UWSNs), primarily due to the extremely low data rate of underwater communication ...

Most learning-based speech enhancement pipelines depend on paired clean–noisy recordings, which are expensive or impossible to collect at scale in real-world conditions. Unsupervised routes like ...

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Abstract: In this letter, we propose a deep learning-based iterative residual encoder-decoder method (IRED), which provides an efficient deep learning framework for electromagnetic modeling over a ...

ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...

I am currently doing a small research for my study on Sparse Transfer Learning and SparseML library is a good approach for my work. My topic is about applying sparse transfer learning on different ...