Remove Categorization Remove Computer Vision Remove Explainability Remove Explainable AI
article thumbnail

Advancing Human-AI Interaction: Exploring Visual Question Answering (VQA) Datasets

Heartbeat

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. or Visual Question Answering version 2.0,

article thumbnail

Bias Detection in Computer Vision: A Comprehensive Guide

Viso.ai

Bias detection in Computer Vision (CV) aims to find and eliminate unfair biases that can lead to inaccurate or discriminatory outputs from computer vision systems. Computer vision has achieved remarkable results, especially in recent years, outperforming humans in most tasks. Let’s get started.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Computer Vision Tasks (Comprehensive 2024 Guide)

Viso.ai

Computer vision (CV) is a rapidly evolving area in artificial intelligence (AI), allowing machines to process complex real-world visual data in different domains like healthcare, transportation, agriculture, and manufacturing. Future trends and challenges Viso Suite is an end-to-end computer vision platform.

article thumbnail

Showcasing the Power of AI in Investment Management: a Real Estate Case Study

DataRobot Blog

In this educated example , the aim is to predict home prices at the property level in the city of Madrid and the training dataset contains 5 different data types (numerical, categorical, text, location, and images) and +90 variables that are related to these 5 different groups: Market performance. Property performance. Property features.

article thumbnail

The most important AI trends in 2024

IBM Journey to AI blog

The incoming generation of interdisciplinary models, comprising proprietary models like OpenAI’s GPT-4V or Google’s Gemini, as well as open source models like LLaVa, Adept or Qwen-VL, can move freely between natural language processing (NLP) and computer vision tasks.

AI 238