concept

computer vision

Also known as: computer vision technology, machine vision

Facts (15)

Sources

Unlocking the Potential of Generative AI through Neuro-Symbolic ... arxiv.org arXiv Feb 16, 2025 2 facts

claimNeural networks (NNs) are capable of acquiring sophisticated patterns and representations from voluminous datasets, which has led to breakthroughs in disciplines such as computer vision, speech recognition, and natural language processing.

procedureThe detect-understand-act (DUA) framework operates in three stages: the detect module uses computer vision to process unstructured data into symbolic representations; the understand component uses answer set programming (ASP) and inductive logic programming (ILP) to ensure decisions align with symbolic rules; and the act component uses pre-trained reinforcement learning policies to refine symbolic representations.

Track: Poster Session 3 - aistats 2026 virtual.aistats.org Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche · AISTATS 2 facts

claimMulti-task representation learning is widely used in deep learning applications, including computer vision and natural language processing, due to its generalization performance.

measurementThe computer vision model compression approach developed by the authors compresses model parameters by approximately 50× and reduces model size by 75% on CIFAR-10, CIFAR-100, and ImageNet1k benchmarks, while maintaining accuracy and uncertainty estimations comparable to state-of-the-art methods.

A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Springer Dec 9, 2025 2 facts

claimNeuro-symbolic AI in computer vision bridges low-level perceptual tasks with high-level cognitive reasoning, enabling systems to understand and reason about visual scenes in a human-like manner.

referenceGojić, Vincan, Kundačina, Mišković, and Dragan (2023) examine non-adversarial robustness in deep learning methods applied to computer vision.

Understanding LLM Understanding skywritingspress.ca Skywritings Press Jun 14, 2024 2 facts

accountAlexei Efros conducts research on data-driven computer vision, computer graphics, and computational photography, specifically utilizing large amounts of unlabelled visual data to understand, model, and recreate the visual world.

perspectiveAlexei Efros, a professor of electrical engineering and computer science at UC Berkeley, asserts that the field of computer vision has historically focused on algorithms and models while treating data as an afterthought, though the discipline has recently begun to appreciate the crucial role of data.

How NATO can integrate AI to prevail in future algorithmic warfare atlanticcouncil.org Atlantic Council 4 days ago 2 facts

referenceMilitary classification models are currently used for computer vision, facial and object recognition, and behavior detection, allowing for the identification of vehicles, aircraft, ships, and infrastructure in imagery from satellites, aircraft, and unmanned aerial systems (UASs).

claimAdvances in machine vision allow drones to determine their position without relying on global navigation satellite systems by comparing real-time imagery from downward-facing cameras with stored satellite images and inertial data.

Open source software best practices and supply chain risk ... - GOV.UK gov.uk Department for Science, Innovation and Technology Mar 3, 2025 1 fact

claimNVIDIA open-sourced PhysX because physics simulation is foundational to AI, robotics, and computer vision, and open-sourcing allowed for wider development and application than NVIDIA could achieve alone.

Construction and Evaluation of an "AI+Knowledge Graph" Teaching ... researchsquare.com Research Square 1 fact

claimThe study designed an 'AI+Knowledge Graph' teaching model based on the ARCS motivation model, which incorporates five core functional modules: learning resources, classroom teaching, teacher-student interaction, formative assessment, and computer vision technology.

Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org arXiv 1 fact

referenceThe ImageNet Large Scale Visual Recognition Challenge is a benchmark for computer vision, documented by Russakovsky et al. in the International Journal of Computer Vision in 2015.

Beyond Missile Deterrence: The Rise of Algorithmic Superiority trendsresearch.org Trends Research & Advisory Mar 16, 2026 1 fact

claimAI-powered computer vision allows unmanned aerial vehicles (UAVs) to detect, classify, and track vehicles, personnel, and infrastructure, reducing the human effort required for image analysis and enabling continuous monitoring of contested areas.

Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org arXiv 1 fact

claimIn computer vision, NeuroSymbolic AI is applied to grounded language learning and utilizes datasets like CLEVERER-Humans to present trust-related challenges for AI systems.