Abstract: To carry out cell counting, it is common to use neural network models with an encoder-decoder structure to generate regression density maps. In the encoder-decoder structure, skip ...

We propose an encoder-decoder for open-vocabulary semantic segmentation comprising a hierarchical encoder-based cost map generation and a gradual fusion decoder. We introduce a category early ...

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 ...

SHallow REcurrent Decoder-based Reduced Order Model (SHRED-ROM) is an ultra-hyperreduced order modeling framework aiming at reconstructing high-dimensional data from limited sensor measurements in ...

Abstract: Change detection is a critical task in earth observation applications. Recently, deep-learning-based methods have shown promising performance and are quickly adopted in change detection.

In a public debate, Adam Brown argued that scaling current language models can lead to increasingly capable systems, while Yann LeCun countered that token prediction cannot capture the continuous, ...

On a mountaintop better known for sunrise selfies, UH Mānoa scientists are quietly teaching a computer to unravel the Sun. Their new artificial intelligence tool peels back the star’s tangled magnetic ...

An automatic toll gate system using Arduino revolutionises traditional toll collection by eliminating manual intervention. The “automatic toll gate system project” demonstrates how simple sensors and ...

Chinese AI companies are recruiting Kenyan workers informally through WhatsApp groups to label large volumes of video data—without contracts, for about $5.42 per shift lasting up to 12 hours, while ...