Results 141 to 150 of about 61,624 (324)
Developmental Science, Volume 29, Issue 2, March 2026.ABSTRACT The comprehension–production vocabulary gap is a well‐documented hallmark of language development; however, anecdotal evidence suggests that this asymmetry may be reduced in children with Williams syndrome (WS). Here, we use empirical data to characterise the comprehension–production gap and computational modelling to investigate potential ...
Dean D'Souza +3 more
wiley +1 more source
RecLVQ: Recurrent Learning Vector Quantization
ESANN 2021 proceedings, 2021 Jensun Ravichandran +2 more
openaire +1 more source
Expert Systems, Volume 43, Issue 3, March 2026.ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam +3 more
wiley +1 more source
Learning vector quantization with adaptive metrics for online figure-ground segmentation
, 2009 Edgar Körner
openalex +1 more source
Explaining Reject Options of Learning Vector Quantization Classifiers [PDF]
, 2022 André Artelt +3 more
openalex +1 more source
Clustering of Longitudinal Data: A Tutorial on a Variety of Approaches
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 1, February 2026.ABSTRACT During the past two decades, methods for identifying groups with different trends in longitudinal data involving a single numeric outcome have become of increasing interest across many areas of research. To support researchers, we summarize the guidance from literature regarding the clustering of such data.
N. G. P. Den Teuling +2 more
wiley +1 more source
Using Of Learning Vector Quantization Network for Pan Evaporation Estimation
Tikrit Journal of Engineering Sciences, 2013 A modern technique is presented to study the evaporation process which is considered as an important component of the hydrological cycle. The Pan Evaporation depth is estimated depending upon four metrological factors viz. (temperature, relative humidity,
Kamil7 A. Abdulmohsen, Iftikar A. Al Ani
doaj
Testing Audio Compression Autoencoders for Seismology: Moving Toward Foundation Models
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.Abstract Efforts to develop foundation models (FMs) for seismic waveform analysis are beginning to advance with progress still needed for geophysics applications. FMs learn a generalized representation of the data using a self‐supervised approach, thus allowing several downstream tasks to be performed in a unified framework.
Laura Laurenti +5 more
wiley +1 more source
Proportional Learning Vector Quantization
Journal of Japan Society for Fuzzy Theory and Systems, 1998 Rui-Ping LI, Masao MUKAIDONO
openaire +2 more sources