Search Results for "raw"

...SentencePiece implements subword units (e.g., byte-pair-encoding (BPE) [Sennrich et al.]) and unigram language model [Kudo.]) with the extension of direct training from raw sentences. SentencePiece allows us to make a purely end-to-end system that does not depend on language-specific pre/postprocessing. Purely data driven, sentencePiece trains tokenization and detokenization models from sentences. Pre-tokenization (Moses tokenizer/MeCab/KyTea) is not always required. SentencePiece treats the sentences just as sequences of Unicode characters. ...

AsmJit is a low-level code generation library designed for dynamically creating machine code at runtime, enabling just-in-time (JIT) compilation for performance-critical applications. It provides a high-level API that abstracts away the complexity of writing raw assembly while still allowing fine-grained control over instruction generation. The library supports multiple architectures, including x86 and x64, making it versatile for cross-platform development. It is commonly used in applications such as emulators, compilers, and high-performance computing systems where runtime optimization is essential. asmjit emphasizes low latency and efficiency, ensuring that generated code executes quickly without significant overhead. ...

...It provides pre-built modules and optimized pipelines for tasks such as object detection, image transformation, and feature extraction, reducing the need for low-level implementation. The framework is designed to be more developer-friendly than raw OpenCV by offering cleaner APIs and reusable components that accelerate development. It supports integration with machine learning models, enabling hybrid workflows that combine traditional computer vision techniques with modern AI approaches. SmartOpenCV is suitable for applications such as robotics, surveillance, augmented reality, and image analysis, where efficient and reliable processing is required. ...

...We do not yet have a full system that can extract facts from arbitrary text, but we have built a number of the subsystems needed for such a system. The SLING frame store is our basic framework for building and manipulating frame semantic graph structures. The Wiki flow pipeline can take a raw dump of Wikidata and convert this into one big frame graph.

Convolutional Recurrent Neural Network provides an implementation of the Convolutional Recurrent Neural Network (CRNN) architecture, a deep learning model designed for image-based sequence recognition tasks such as optical character recognition and scene text recognition. The architecture combines convolutional neural networks for extracting visual features from images with recurrent neural networks that model sequential dependencies in the extracted features. This hybrid approach allows the...

A tool that helps develope the course of cognitive thought processes through software. This tool will look at the raw hex code of any input. It establishes pattern recognition over a mesured time incrament that in itself is at a different pace.