Gradient-Based Learning Applied to Document Recognition

GPTKB entity

Statements (44)
Predicate Object
gptkbp:instance_of gptkb:Research_Institute
gptkbp:bfsLayer 3
gptkbp:bfsParent gptkb:Yann_Le_Cun
gptkbp:addresses image processing
gptkbp:analyzes training algorithms
gptkbp:applies_to gradient descent
gptkbp:author gptkb:Yann_Le_Cun
gptkbp:collaborations multiple authors
gptkbp:contains mathematical models
gptkbp:contributed_to gptkb:software_framework
gptkbp:discusses feature extraction
gptkbp:exhibited_at high accuracy
gptkbp:explores convolutional networks
gptkbp:focuses_on document recognition
gptkbp:gift_shop case studies
gptkbp:has_impact_on AI development
https://www.w3.org/2000/01/rdf-schema#label Gradient-Based Learning Applied to Document Recognition
gptkbp:includes gptkb:experimental_results
gptkbp:influences computer vision
gptkbp:involves data preprocessing
gptkbp:is_associated_with Yann Le Cun's research
gptkbp:is_available_in academic databases
gptkbp:is_cited_in over 500 times
machine learning textbooks
gptkbp:is_compared_to traditional methods
gptkbp:is_discussed_in gptkb:academic_conferences
gptkbp:is_evaluated_by peer review
gptkbp:is_influenced_by statistical learning theory
gptkbp:is_part_of computer science curriculum
machine learning literature
gptkbp:is_recognized_by seminal work
gptkbp:is_referenced_in numerous subsequent studies
gptkbp:is_related_to pattern recognition
gptkbp:is_supported_by empirical evidence
gptkbp:is_used_in automated systems
gptkbp:provides theoretical foundations
gptkbp:published_by gptkb:API
gptkb:IEEE_Transactions_on_Pattern_Analysis_and_Machine_Intelligence
gptkbp:suitable_for future research directions
gptkbp:user_reviews literature on document recognition
gptkbp:uses gptkb:microprocessor
gptkbp:utilizes backpropagation
gptkbp:written_in English
gptkbp:year gptkb:1998