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Toplam kayıt 11, listelenen: 1-10
Multi-Scale Hierarchical Topology Optimization for Nanophotonic Design
(Optics InfoBase Conference Papers, 2020)
We develop a multi-scale method to rapidly design efficient and fabricationcompatible
nanophotonic devices, and demonstrate it by designing a mode multiplexer
with 98.1% efficiency in 104 iterations under 50 seconds using ...
Recommending Healthy Meal Plans by Optimising Nature-Inspired Many-Objective Diet Problem
(SAGE, 2021)
Healthy eating is an important issue affecting a large part of the world population, so human diets are
becoming increasingly popular, especially with the devastating consequences of Coronavirus Disease
(Covid-19). A ...
A Novel Collective Crossover Operator for Genetic Algorithms
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Crossover is the main genetic operator which influences
the power of evolutionary algorithms. Among a variety
of crossover operators, there has been a growing interest in
multi-parent crossover operators in evolutionary ...
A Deep Learning Model for Automated Segmentation of Fluorescence Cell images
(IOP Publishing Ltd, 2021)
Deep learning techniques bring together key advantages in biomedical image
segmentation. They speed up the process, increase the reproducibility, and reduce the workload
in segmentation and classification. Deep learning ...
Experimental Evaluation of Meta-Heuristics for Multi-Objective Capacitated Multiple Allocation Hub Location Problem
(Elsevier, 2022)
Multi-objective capacitated multiple allocation hub location problem (MOCMAHLP) is a variation of classic
hub location problem, which deals with network design, considering both the number and the location
of the hubs ...
DeepCAN: A Modular Deep Learning System for Automated Cell Counting and Viability Analysis
(IEEE, 2022)
Precise and quick monitoring of key cytometric features such as cell count, cell size, cell morphology,
and DNA content is crucial for applications in biotechnology, medical sciences, and cell culture research. Traditionally, ...
Empirical Comparison of Heuristic Optimisation Methods for Automated Car Setup
(Sprınger, 2022)
Tuning a race car to improve its performance by adopting an effective
setup is crucial and an extremely challenging task. The Open Racing Car Simulator,
referred to as TORCS, is a well-known simulator in which a race car ...
Neural Architecture Search Using Metaheuristics for Automated Cell Segmentation
(Springer, 2023)
Deep neural networks give successful results for segmentation of medical images. The need for optimizing many hyper-parameters
presents itself as a significant limitation hampering the effectiveness of
deep neural network ...
Differential Evolution-Based Neural Architecture Search for Brain Vessel Segmentation
(Elsevier, 2024)
Brain vasculature analysis is critical in developing novel treatment targets for neurodegenerative diseases.
Such an accurate analysis cannot be performed manually but requires a semi-automated or fully-automated
approach. ...
Evolutionary Architecture Optimization for Retinal Vessel Segmentation
(IEEE, 2023)
Retinal vessel segmentation (RVS) is crucial
in medical image analysis as it helps identify and monitor
retinal diseases. Deep learning approaches have shown
promising results for RVS, but designing optimal neural
network ...