IEEE

DE-Unet: Dual-Encoder U-Net for Ultra-High Resolution Remote Sensing Image Segmentation

Abstract: In recent years, there has been a growing demand for remote sensing image semantic segmentation in various applications. The key to semantic segmentation lies in the ability to globally ...
EurekAlert!

AI boosts understanding of ocean dynamics and marine structure safety

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...
EurekAlert!

CornPheno: A game-changer in corn breeding with smartphone-based phenotyping

Corn is one of the world's most important crops, critical for food, feed, and industrial applications. In 2023, corn ...
IEEE

Leveraging Machine Learning Approaches to Decode Hive Sounds for Stress Prediction

Abstract: Beekeeping plays a vital role in preserving ecosystems through pollination and increasing biodiversity. Effective monitoring of honeybee health and hive conditions is essential to balance ...
marktechpost

Google Introduces T5Gemma 2: Encoder Decoder Models with Multimodal Inputs via SigLIP and 128K Context

T5Gemma 2 follows the same adaptation idea introduced in T5Gemma, initialize an encoder-decoder model from a decoder-only checkpoint, then adapt with UL2. In the above figure the research team show ...
GitHub

Zero-Training Context Extension for Transformer Encoders via Nonlinear Absolute Positional Embeddings Interpolation

Official implementation of "Zero-Training Context Extension for Transformer Encoders via Nonlinear Absolute Positional Embeddings Interpolation". Paper preprint is coming soon. This implementation ...
Frontiers

Robust automated preclinical fMRI preprocessing via a multi-stage dilated convolutional Swin Transformer affine registration

Introduction: Accurate preprocessing of functional magnetic resonance imaging (fMRI) data is crucial for effective analysis in preclinical studies. Key steps such as denoising, skull-stripping, and ...