# 3.7 Terms related to computer vision, ISO 22989 Published contents Contents1 Scope2 Normative references3 Terms and definitions4 Abbreviated terms5 AI conceptsClause 3, terms 3.1 Terms related to AI3.1.1 AI agent3.1.2 AI component3.1.3 artificial intelligence3.1.4 artificial intelligence system3.1.5 autonomy3.1.6 application specific integrated circuit3.1.7 automatic3.1.8 cognitive computing3.1.9 continuous learning3.1.10 connectionism3.1.11 data mining3.1.12 declarative knowledge3.1.13 expert system3.1.14 general AI3.1.15 genetic algorithm3.1.16 heteronomy3.1.17 inference3.1.18 internet of things3.1.19 IoT device3.1.20 IoT system3.1.21 knowledge3.1.22 life cycle3.1.23 model3.1.24 narrow AI3.1.25 performance3.1.26 planning3.1.27 prediction3.1.28 procedural knowledge3.1.29 robot3.1.30 robotics3.1.31 semantic computing3.1.32 soft computing3.1.33 symbolic AI3.1.34 subsymbolic AI3.1.35 task3.2 Terms related to data3.2.1 data annotation3.2.2 data quality checking3.2.3 data augmentation3.2.4 data sampling3.2.5 dataset3.2.6 exploratory data analysis3.2.7 ground truth3.2.8 imputation3.2.9 input data3.2.10 label3.2.11 personally identifiable information3.2.12 production data3.2.13 sample3.2.14 test data3.2.15 validation data3.3 Terms related to machine learning3.3.1 Bayesian network3.3.2 decision tree3.3.3 human-machine teaming3.3.4 hyperparameter3.3.5 machine learning3.3.6 machine learning algorithm3.3.7 machine learning model3.3.8 parameter3.3.9 reinforcement learning3.3.10 retraining3.3.11 semi-supervised machine learning3.3.12 supervised machine learning3.3.13 support vector machine3.3.14 trained model3.3.15 training3.3.16 training data3.3.17 unsupervised machine learning3.4 Terms related to neural networks3.4.1 activation function3.4.2 convolutional neural network3.4.3 convolution3.4.4 deep learning3.4.5 exploding gradient3.4.6 feed forward neural network3.4.7 long short-term memory3.4.8 neural network3.4.9 neuron3.4.10 recurrent neural network3.5 Terms related to trustworthiness3.5.1 accountable3.5.2 accountability3.5.3 availability3.5.4 bias3.5.5 control3.5.6 controllability3.5.7 explainability3.5.8 predictability3.5.9 reliability3.5.10 resilience3.5.11 risk3.5.12 robustness3.5.13 stakeholder3.5.14 transparency3.5.15 transparency3.5.16 trustworthiness3.5.17 verification3.5.18 validation3.6 Terms related to natural language processing3.6.1 automatic summarization3.6.2 dialogue management3.6.3 emotion recognition3.6.4 information retrieval3.6.5 machine translation3.6.6 named entity recognition3.6.7 natural language3.6.8 natural language generation3.6.9 natural language processing3.6.10 natural language processing3.6.11 natural language understanding3.6.12 optical character recognition3.6.13 part-of-speech tagging3.6.14 question answering3.6.15 relationship extraction3.6.16 sentiment analysis3.6.17 speech recognition3.6.18 speech synthesis3.7 Terms related to computer vision3.7.1 computer vision3.7.2 face recognition3.7.3 image3.7.4 image recognitionClause 5, concepts 5.1 General5.2 From strong and weak AI to general and narrow AI5.3 Agent5.4 Knowledge5.5 Cognition and cognitive computing5.6 Semantic computing5.7 Soft computing5.8 Genetic algorithms5.9 Symbolic and subsymbolic approaches for AI5.10 Data5.11 Machine learning concepts Home / Clauses Terms related to computer vision · 3.7 # Terms related to computer vision Four entries cover vision: computer vision itself, face recognition, the digital image and image recognition. They matter to a governance lead because image and video data raise a different evidence and privacy pattern from text. - terms and definitions - Clause - ISO/IEC 22989:2022/FDAmd 1 - Last updated: 2026-10-21 ## What this clause settles The page is a reading of the published structure and the public entries. It does not invent the body of a clause that ISO has not published, and it does not turn a heading into an obligation. For Terms related to computer vision, the page keeps the claim level "terms and definitions" visible and says where the public text stops. ## Who it binds The organisation that adopts the vocabulary. The clause is not a shall requirement; the claim level states what it is. ## What to do in your practice Take the clause into the next governance review with two questions: which artefacts rely on it, and which sentence would a reviewer quote to show the firm uses it? Record the answers as actions with dates. Start with the artefacts that cite Terms related to computer vision and work outwards. ## Evidence an auditor or regulator asks for - A policy map that names Terms related to computer vision and the clause it comes from. Shows that Terms related to computer vision was read and placed, not merely cited. - A controlled vocabulary register for the entries in Terms related to computer vision, with an owner and a review date. An auditor asks who keeps the Terms related to computer vision entries current, not only whether they exist. - One live artefact that uses a term from Terms related to computer vision correctly, with the date it was checked. Connects Terms related to computer vision to the work rather than to a shelf document. Ask your teamWhich artefact in the firm relies on Terms related to computer vision, and who keeps it current? ## Common gaps this page catches - Terms related to computer vision is cited without the entries behind it, so the citation cannot be tested. - The clause is treated as a checklist when it is a vocabulary, and counting terms is not the same as controlling them. ## What to prepare before the amendment lands Take Terms related to computer vision into the next review, list the artefacts that rely on it and give each a named owner. The Terms related to computer vision list is the plan; the owner is the control. ## How to test it here Take one live artefact rather than a template, find the sentence or field where Terms related to computer vision is used, and put this page beside it. Record the answer, the artefact and the date, because that record is the evidence and a glossary entry on its own is only an intention. ## What this page does not claim The page does not reproduce the standard, certify the firm or predict the wording the amendment will use; it states Terms related to computer vision at the claim level "terms and definitions" and stops where the public record stops. ## Common questions What does Terms related to computer vision mean in ISO 22989? Four entries cover vision: computer vision itself, face recognition, the digital image and image recognition. They matter to a governance lead because image and video data raise a different evidence and privacy pattern from text. What evidence should we keep for 3.7? A policy map that names Terms related to computer vision and the clause it comes from. A controlled vocabulary register for the entries in Terms related to computer vision, with an owner and a review date. Is Terms related to computer vision a requirement? No: Terms related to computer vision is a definition or clause of a terminology standard, and it becomes binding only when a firm writes it into a policy, a contract or a procedure, or when another standard incorporates it. ## Related units - 3.7.1 computer vision - 3.7.2 face recognition - 3.7.3 image Source. ISO/IEC 22989:2022, Clause 3.7. Open the ISO public entry. Retrieved 21 October 2026. https://www.iso.org/obp/ui/en/#iso:std:iso-iec:22989:ed-1:v1:en ISO catalogue record 88145, the amendment status, stage and dates. Catalogue record 74296, the base standard. Claim level: terms and definitions. All 4 entries are in the public preview. Built from the public ISO record and the public clause 3 entries. No clause text is reproduced. How the record is built. Last updated: 2026-10-21 · Markdown version · Check your vocabulary Source: https://iso-22989-revision-checker.theartofservice.com/clauses/terms-related-to-computer-vision/