Generalisable 3D printing error detection and correction via multi-head neural networks. [PDF]
Material extrusion is the most widespread additive manufacturing method but its application in end-use products is limited by vulnerability to errors. Humans can detect errors but cannot provide continuous monitoring or real-time correction.
Brion DAJ, Pattinson SW.
europepmc +2 more sources
Not all grammar errors are equally noticed: error detection of naturally occurring errors and implications for eye-tracking models of everyday texts [PDF]
Grammar errors are a natural part of everyday written communication. They are not a uniform group, but vary from morphological errors to ungrammatical word order and involve different types of word classes. In this study, we examine whether some types of
Katrine Falcon Søby +2 more
doaj +2 more sources
Hybrid Pipeline Hardware Architecture Based on Error Detection and Correction for AES [PDF]
Currently, cryptographic algorithms are widely applied to communications systems to guarantee data security. For instance, in an emerging automotive environment where connectivity is a core part of autonomous and connected cars, it is essential to ...
Ignacio Algredo-Badillo +4 more
doaj +2 more sources
An Unsupervised Error Detection Methodology for Detecting Mislabels in Healthcare Analytics [PDF]
Medical datasets may be imbalanced and contain errors due to subjective test results and clinical variability. The poor quality of original data affects classification accuracy and reliability.
Pei-Yuan Zhou +6 more
doaj +2 more sources
Enhancing Error Detection on Medical Knowledge Graphs via Intrinsic Label [PDF]
The construction of medical knowledge graphs (MKGs) is steadily progressing from manual to automatic methods, which inevitably introduce noise, which could impair the performance of downstream healthcare applications.
Guangya Yu, Qi Ye, Tong Ruan
doaj +2 more sources
Advancing passive BCIs: a feasibility study of two temporal derivative features and effect size-based feature selection in continuous online EEG-based machine error detection [PDF]
The emerging integration of Brain-Computer Interfaces (BCIs) in human-robot collaboration holds promise for dynamic adaptive interaction. The use of electroencephalogram (EEG)-measured error-related potentials (ErrPs) for online error detection in ...
Yanzhao Pan +4 more
doaj +2 more sources
xcomet: Transparent Machine Translation Evaluation through Fine-grained Error Detection [PDF]
Widely used learned metrics for machine translation evaluation, such as Comet and Bleurt, estimate the quality of a translation hypothesis by providing a single sentence-level score.
Nuno M. Guerreiro +5 more
semanticscholar +1 more source
Protecting expressive circuits with a quantum error detection code [PDF]
A successful quantum error correction protocol would allow quantum computers to run algorithms without suffering from the effects of noise. However, fully fault-tolerant quantum error correction is too resource intensive for existing quantum computers ...
C. Self, Marcello Benedetti, D. Amaro
semanticscholar +1 more source
Annotation Error Detection: Analyzing the Past and Present for a More Coherent Future [PDF]
Annotated data is an essential ingredient in natural language processing for training and evaluating machine learning models. It is therefore very desirable for the annotations to be of high quality.
Jan-Christoph Klie +2 more
semanticscholar +1 more source
Contrastive Knowledge Graph Error Detection [PDF]
Knowledge Graph (KG) errors introduce non-negligible noise, severely affecting KG-related downstream tasks. Detecting errors in KGs is challenging since the patterns of errors are unknown and diverse, while ground-truth labels are rare or even ...
Qinggang Zhang +5 more
semanticscholar +1 more source

