Vega, R. Madarshahian and M. D. Todd, A neural network surrogate model for structural health monitoring ... H. Kim and H. Kim, Encoder-decoder network for pixel-level road crack ... G. Yang, J. Q. Li, ...

Many computational methods have been proposed to predict drug–drug interactions (DDIs), which can occur when combining drugs to treat various diseases, but most mainly utilize single-source features ...

The study draws parallels between natural language and genomic sequences, training LLMs to understand and predict gene functions, regulatory elements, and expression patterns in plants. Different LLM ...

Scaling up Artificial Intelligence (AI) algorithms for massive datasets to improve their performance is becoming crucial. In Machine Translation (MT), one of most important research fields of AI, ...

Next-generation U-Net Encoder: Decoder for accurate, automated CTC detection from images of peripheral blood nucleated cells stained with EPCAM and DAPI. Authors: ... Results: Analysis of total 1564 ...

Encoder-Decoder models handle tasks like translation by encoding input and decoding output, with distinct architectures. Positional encoding happens once, before layer 1, to embed sequence order. LoRA ...

The existing deep learning based reversible data hiding (RDH) predictors typically adopt standard convolutions for extracting features, which inherently fails to capture contextual information across ...