A new hybrid optimization method combining moth–flame optimization and teaching–learning-based optimization algorithms for visual tracking
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-020-05032-1.pdf
Reference60 articles.
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2. Barham R, Sharieh A, Sleit A (2019a) Multi-moth flame optimization for solving the link prediction problem in complex networks. Springer, Berlin
3. Barham RS, Sharieh A, Sleit A (2019b) A meta-heuristic framework based on clustering and preprocessed datasets for solving the link prediction problem. J Inf Sci 45:794–817. https://doi.org/10.1177/0165551518816296
4. Bhesdadiya RH, Trivedi IN, Jangir P et al (2017) A novel hybrid approach particle swarm optimizer with Moth–Flame optimizer algorithm. Adv Intell Syst Comput 553:569–577. https://doi.org/10.1007/978-981-10-3770-2_53
5. Cheng G, Yang C, Yao X et al (2018) When deep learning meets metric learning: remote sensing image scene classification via learning discriminative CNNs. IEEE Trans Geosci Remote Sens 56:2811–2821. https://doi.org/10.1109/TGRS.2017.2783902
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