Scene text recognition using vision-based text recognition
Scene Text Recognition (STR) continues to challenge researchers due to the diversity of text occurrences in natural environments. It is ...
Tag: Text
Optimizing LLM for Long Text Inputs and Chat Applications
Large Language Models (LLMs) have revolutionized characteristic dialect preparing (NLP), fueling applications extending from summarization and interpretation to conversational operators ...
Jina AI Introduces Jina-CLIP v2: A 0.9B Multilingual Multimodal Embedding Model Connecting Images with Text in 89 Languages
In an interconnected world, effective communication in multiple languages and media is increasingly important. Multimodal ai faces challenges in combining ...
Build cost-effective RAG applications with binary embeddings on Amazon Titan Text Embeddings V2, Amazon OpenSearch Serverless, and Amazon Bedrock knowledge bases
Today, we are pleased to announce the availability of Binary Embeddings for amazon Titan Text Embeddings V2 in amazon Bedrock ...
Fine-tune multimodal models for vision and text use cases on Amazon SageMaker JumpStart
In the rapidly evolving landscape of ai, generative models have emerged as a transformative technology, empowering users to explore new ...
Fine-tune Meta Llama 3.2 text generation models for generative AI inference using Amazon SageMaker JumpStart
Generative ai models have seen tremendous growth, offering cutting-edge solutions for text generation, summarization, code generation, and question answering. Despite ...
CtrlSynth: Controllable image and text synthesis for data-efficient multimodal learning
Pre-training of robust or multimodal baseline vision models (e.g., CLIP) relies on large-scale data sets that can be noisy, potentially ...
Google DeepMind Introduces Omni×R: A Comprehensive Evaluation Framework to Compare the Reasoning Capabilities of Omnimodal Language Models on Text, Audio, Image, and Video Inputs
Omnimodal language models (OLMs) are a rapidly advancing area of ai that enables understanding and reasoning across multiple types of ...
Powering backbone models for visual text generation with input granularity control and glyph recognition training
Generating accurate and aesthetically appealing visual texts in text-to-image generation models presents a significant challenge. While diffusion-based models have succeeded ...
How to use R for text mining
Editor's Image | Ideogram Text mining helps us obtain important information from large amounts of text. R is a useful ...
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