Results 301 to 310 of about 58,206,617 (356)

Potential of RT, bagging and RS ensemble learning algorithms for reference evapotranspiration prediction using climatic data-limited humid region in Bangladesh

, 2020
Ensemble learning (EL), an alternative approach in the machine-learning field, offers an accurate reference evapotranspiration (ETo) prediction, which is of paramount significance for the hydrological studies and agricultural water practices.
Roquia Salam, A. Islam
semanticscholar   +1 more source

GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments

arXiv.org
The era of foundation models has revolutionized AI research, yet Graph Foundation Models (GFMs) remain constrained by the scarcity of large-scale graph corpora.
Enjun Du, Xunkai Li, Tian Jin, Zhihan Zhang, Ronghua Li, Guoren Wang   +5 more
semanticscholar   +1 more source

Support for Big Data's Limiting Resource

Proceedings of the 2014 Workshop on Human Centered Big Data Research, 2014
With an increase in data volume, variety, and velocity, Big Data advances tend to focus on technologies such as data gathering, processing, data storage, and analytics, all of which assume that technology is the limiting factor in leveraging Big Data to its fullest potential.
Samantha Szymczak, Daniel J. Zelik, Wiliam Elm   +2 more
openaire   +1 more source

The Attentional Blink is Immune to Masking-Induced Data Limits

The Quarterly Journal of Experimental Psychology Section A, 2001
The attentional blink is the robust finding that processing a masked item (T1) hinders the subsequent identification of a backwards masked second item (T2), which follows soon after the first one. There has been some debate about the theoretically important relation between the difficulty of T1 processing and the ensuing blink.
E N, McLaughlin, D I, Shore, R M, Klein
openaire   +2 more sources

Taking Data Limitations into Account

Economic & Political Weekly
,
null Taru Saigal, null Sreedevi R S, null Maya K, null Vivek Kumar   +3 more
openaire   +1 more source

Statistical aspects of multilayer perceptrons under data limitations

Computational Statistics & Data Analysis, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Janette F. Walde, Gottfried Tappeiner, Ulrike Tappeiner, Erich Tasser, Hans Werner Holub   +4 more
openaire   +1 more source

Improving the productivity-susceptibility analysis to assess data-limited fisheries

, 2020
Each year, millions of marine aquarium fish and invertebrates are harvested from coral reefs and enter the complex and largely unregulated marine aquarium trade (MAT). It is challenging to identify species at risk of overexploitation in this trade due to
Gabrielle A Baillargeon, M. Tlusty, E. Dougherty, A. Rhyne   +3 more
semanticscholar   +1 more source

Data-Limited Modulation Classification With a CVAE-Enhanced Learning Model

IEEE Communications Letters, 2020
The modulation classification problem can be effectively handled by modern machine learning techniques, however, the available data for training is usually limited due to costly measurements in practice.
Xuefei Ji, Jue Wang, Ye Li, Qiang Sun, Shi Jin, Tony Q. S. Quek   +5 more
semanticscholar   +1 more source

The stock assessment theory of relativity: deconstructing the term “data-limited” fisheries into components and guiding principles to support the science of fisheries management

Reviews in Fish Biology and Fisheries, 2023
J. Cope, N. Dowling, S. A. Hesp, Kristen L. Omori, P. Bessell-Browne, L. Castello, R. Chick, Dawn T. Dougherty, S. Holmes, R. McGarvey, D. Ovando, J. Nowlis, J. Prince   +12 more
semanticscholar   +1 more source

Modelling pulse fishery systems in data-limited situations

, 2020
Per-recruit models have been widely used since the onset of modern fisheries science, particularly in data-limited situations. When the study fishery is a pulse fishery, namely a fishery operating over a brief period followed by a long fallow period ...
A. Grüss, D. Bolser, B. Erisman
semanticscholar   +1 more source