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 ...

Abstract: To create error-free digital data transfer, this investigation outlines the design of a Hamming code encoder and decoder circuit that combines inverter-based pass transistor logic and CNTFET ...

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, ...

Microsoft Word is jam-packed with features and formatting options. It also has numerous ways for users to add shapes, diagrams, and other visual elements to regular word processing templates. But even ...

CNNs are specialized deep neural networks for processing data with a grid-like topology, such as images. A CNN automatically detects the important features without any human supervision. They are ...

Abstract: We have realized a novel optical encoder/decoder on a PLC for time-spreading/wavelength-hopping OCDMA. It was composed of an AWG and sixteen delay lines ...

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 ...

Traditional binary combinational logic circuits are generally obtained by cascading multiple basic logic gate circuits, using more components and complicated wiring. In contrast to the binary logic ...

The GPT family of models process text using tokens, which are common sequences of characters found in text. The models understand the statistical relationships between these tokens, and excel at ...

VVenC and VVdeC are open-source software H.266/VCC video encoder and decoder respectively that are optimized to use SIMD instructions on x86 (SSE42/SIMDe and AVX2) and Arm, and the decoder runs on ...