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 ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...

Abstract: U-shaped encoder-decoder convolutional neural networks have shown significant success in medical image segmentation. However, these networks often face challenges, including detail loss in ...

Abstract: Accurate estimation of two-dimensional (2D) multi-obstacle steady-state flows is crucial in various scientific and engineering disciplines, yet conventional methods often fall short in ...

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Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...

Sipeed MaixBox M4N is an AI box for video analytics and computer vision equipped with an AXera-Pi Pro (AX650N) octa-core Cortex-A55 SoC with a 43.2 TOPS (INT4) or 10.8 TOPS (INT8) AI accelerator and ...

Base64 encoding is a common method to encode binary data into an ASCII string format, making it easier to transmit data over networks that only support text. This can include embedding image data in ...

The Vigènere Cipher is a method of encrypting alphabetic text by using a form of polyalphabetic substitution, which was developed in the 16th century by French cryptographer Blaise de Vigenère. It ...

What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...