Приказ основних података о документу
Putting Humans Back in the Loop: A Study in Human-Machine Cooperative Learning
dc.creator | Gnjatović, Milan | |
dc.creator | Maček, Nemanja | |
dc.creator | Adamović, Saša | |
dc.date.accessioned | 2023-12-06T11:46:14Z | |
dc.date.available | 2023-12-06T11:46:14Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 1785-8860 | |
dc.identifier.uri | http://jakov.kpu.edu.rs/handle/123456789/1516 | |
dc.description.abstract | This paper introduces a novel approach to human-machine collaborative learning that allows for the chronically missing human learnability in the context of supervised machine learning. The basic tenet of this approach is the refinement of a human designed software model through the iterative learning loop. Each iteration of the loop consists of two phases: (i) automatic data-driven parameter adjustment, performed by means of stochastic greedy local search, and (ii) human-driven model adjustment based on insights gained in the previous phase. The proposed approach is demonstrated through a real-life study of automatic electricity meter reading in the presence of noise. Thus, a cognitively-inspired non-connectionist approach to digit detection and recognition is introduced, which is subject to refinement through the iterative process of human-machine cooperation. The prototype system is evaluated with respect to the recognition accuracy (with the highest digit recognition accuracy of 94%), and also discussed with respect to the storage requirements, generalizability, utilized contextual information, and efficiency. | sr |
dc.language.iso | en | sr |
dc.publisher | Budapest : Óbuda University | sr |
dc.rights | restrictedAccess | sr |
dc.source | Acta Polytechnica Hungarica | sr |
dc.subject | human-machine cooperative learning | sr |
dc.subject | digit recognition | sr |
dc.subject | stochastic search | sr |
dc.title | Putting Humans Back in the Loop: A Study in Human-Machine Cooperative Learning | sr |
dc.type | article | sr |
dc.rights.license | ARR | sr |
dc.citation.volume | 17 | |
dc.citation.issue | 2 | |
dc.citation.spage | 191 | |
dc.citation.epage | 210 | |
dc.identifier.doi | 10.12700/APH.17.2.2020.2.11 | |
dc.type.version | publishedVersion | sr |