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This study proposes a novel Weighted Average Deep Ensemble Learning model optimized using the Cuckoo Search Optimization algorithm (Meta-WADE) to address these issues. The model integrates three Deep Convolutional Neural Networks (DCNNs) and two transfer learning models, with their weights optimized via CSO to enhance performance. Extensive experiments on a large dataset of ancient Tamil characters demonstrate the model\u2019s efficacy, achieving state-of-the-art results with an accuracy of 98.85%, precision of 97.11%, recall of 98.90%, and F1 score of 98.00%. 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