In order to address these challenges, we propose a convolutional encoder-decoder model with deep learning for document image binarization in this paper. In the proposed method, mid-level document ...

The three-dimensional world of ordinary experience—the universe filled with galaxies, stars, planets, houses, boulders, and ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

National Key Laboratory of Advanced Micro and Nano Manufacture Technology, Shanghai Jiao Tong University, Shanghai 200240, China Department of Micro/Nano Electronics, School of Electronic Information ...

This paper is the first of its kind to incorporate deep learning into a microtext normalization module and improve the sentiment analysis task. We show our models as a sequence to sequence character ...

A research team from Kumamoto University has developed a promising deep learning model that significantly enhances the accuracy of subgraph matching—a critical task in fields ranging from drug ...

We introduce ACE-Step, a novel open-source foundation model for music generation that overcomes key ... ACE-Step bridges this gap by integrating diffusion-based generation with Sana’s Deep Compression ...

Deep learning has ... for global feature learning has become particularly urgent. To address the aforementioned problem, we propose a global learning network with large receptive fields (GLNet) based ...

aArtificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA bDepartment of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer ...