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TRV-2026-0066Version 3 · Revised

Written 2026-07-12 20:58:07 UTC · current record

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TRUVACE RECORD VERSION
record: TRV-2026-0066
version: 3
kind: revised
reason: Reading revised
timestamp: 2026-07-12T20:58:07.120185Z
status: published
lens: g_space
sector: science
headline: Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition
dek: The era of artificial neural network (ANN) began with a simplified application in many fields and remarkable success in pattern recognition (PR) even in manufacturing industries. Although significant progress achieved and surveyed in addressing ANN application to PR challenges, nevertheless, some problems are yet to be resolved like whimsical orientation (the unknown path that cannot be accurately calculated due to its directional position). Other problem includes; object classification, location, scaling, neuro…
gain_reading: The era of artificial neural network (ANN) began with a simplified application in many fields and remarkable success in pattern recognition (PR) even in manufacturing industries.
problem_reading: (none)
limitation: Historical evidence reading: the cited study may be limited by its design, population, period, or setting, and later research may report different effects.
tag: Evidence-backed gain
key_points: Although significant progress achieved and surveyed in addressing ANN application to PR challenges, nevertheless, some problems are yet to be resolved like whimsical orientation (the unknown path that cannot be accurately calculated due to its directional position). | Other problem includes; object classification, location, scaling, neurons behavior analysis in hidden layers, rule, and template matching. | Also, the lack of extant literature on the issues associated with ANN application to PR seems to slow down research focus and progress in the field.
rundown: The era of artificial neural network (ANN) began with a simplified application in many fields and remarkable success in pattern recognition (PR) even in manufacturing industries. Although significant progress achieved and surveyed in addressing ANN application to PR challenges, nevertheless, some problems are yet to be resolved like whimsical orientation (the unknown path that cannot be accurately calculated due to its directional position).

Other problem includes; object classification, location, scaling, neurons behavior analysis in hidden layers, rule, and template matching. Also, the lack of extant literature on the issues associated with ANN application to PR seems to slow down research focus and progress in the field.
sources:
- peer_reviewed | IEEE Access | https://doi.org/10.1109/access.2019.2945545 | 2019-01-01
- peer_reviewed | IEEE Access | https://doi.org/10.1109/access.2022.3143033 | 2022-01-01
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