The (μ+1) EA optimizes BinVal in O(μ log μ · n log n) evaluations for μ = o(n/log n), improving the prior O(μ^5 n log(n/μ^4)) bound.
In: Proceedings of the IEEE Symposium Series on Computational Intelligence
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A lightweight hybrid CNN-LSTM network classifies bean leaf diseases at 94.38% accuracy and 1.86 MB size on the ibean dataset, with reported state-of-the-art F1 scores using EfficientNet-B7+LSTM.
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Improved Runtime Bound for the $(\mu + 1)$ EA on BinVal
The (μ+1) EA optimizes BinVal in O(μ log μ · n log n) evaluations for μ = o(n/log n), improving the prior O(μ^5 n log(n/μ^4)) bound.
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A Resource-Efficient Hybrid CNN-LSTM network for image-based bean leaf disease classification
A lightweight hybrid CNN-LSTM network classifies bean leaf diseases at 94.38% accuracy and 1.86 MB size on the ibean dataset, with reported state-of-the-art F1 scores using EfficientNet-B7+LSTM.