Results 201 to 210 of about 18,713 (263)

HRL-Det: Hierarchical Reinforcement Learning for Sequential Object Detection in Aerial Imagery. [PDF]

Sensors (Basel)
Li M, Hu Y.
europepmc   +1 more source

Empirical Bayes Covariance Decomposition, and a Solution to the Multiple Tuning Problem in Sparse PCA. [PDF]

J Comput Graph Stat
Kang J, Stephens M.
europepmc   +1 more source

Gradient-Based Efficient Optimization Method for Surface Sensor Arrays in Microseismic Source Mechanism Inversion. [PDF]

Sensors (Basel)
Kong Y, Yuan Y.
europepmc   +1 more source

Detection and classification of lung cancer using sequential hybridization of CNN and RNN type architectures. [PDF]

Front Big Data
Vutukuri M, Habibullah PS.
europepmc   +1 more source

PK-Informed Microphysiological Systems: From Dynamic Dosing to Quantitative In Vitro-In Vivo Translation. [PDF]

Pharmaceutics
Kang SJ, Bong S, Jo MJ, Lee JM, Yoon MS, Park S, Lee Y, Shin Y, Lee HJ, Park CW, Shin DH.   +10 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

A NEW METHOD OF SEQUENTIAL APPROXIMATE OPTIMIZATION FOR STRUCTURAL OPTIMIZATION PROBLEMS

Engineering Optimization, 1995
Abstract In this paper a new method of sequential approximate optimization is introduced to solve some structural optimization problems. This new method employs a new intermediate variable which has two variable parameters to linearize the objective and constraint functions in terms of the intermediate variable.
Zheng-Dong Ma, Noboru Kikuchi
exaly   +2 more sources

Framework for sequential approximate optimization

Structural and Multidisciplinary Optimization, 2004
An object-oriented framework for Sequential Approximate Optimization (SAO) isproposed. The framework aims to provide an open environment for thespecification and implementation of SAO strategies. The framework is based onthe Python programming language and contains a toolbox of Python classes,methods, and interfaces to external software.
Jacobs, J.H., Etman, L.F.P., Keulen, van, F., Rooda, J.E.   +3 more
openaire   +2 more sources

An Object-Oriented Framework for Sequential Approximate Optimization

9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 2002
A sequential approximate optimization method is used to optimize computational expensive or non-smooth output behavior of simulation models. In this paper a flexible and compact object-oriented framework is proposed that supports the implementation and use of a sequential approximate optimization strategy.
Jacobs, J.H., Etman, L.F.P., Keulen, van, A., Rooda, J.E.   +3 more
openaire   +2 more sources