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Palabras clave – provistas por la editorial

artificial intelligence; deep learning; AlphaZero; NoGo games; reinforcement learning; evolutionary algorithm; convolutional neural network; transfer learning; image classification; large-scale multiobjective optimization; sparse unmixing; hyperspectral image; opponent exploitation; no-limit Texas hold’em; neuroevolution; online update; reliable evaluation strategy; active–frozen memory model; visual tracking; evolutionary multitasking; particle swarm optimization; multipopulation optimization; computational intelligence; medical image segmentation; convolutional neural networks; weakly supervised segmentation; attention mechanism; HCNNs; progressive deep learning; disease screening; multi-target tracking; evolutionary optimization; random finite set; joint integrated probabilistic data association; few-shot learning; medical image classification; spatial attention; crop insect pest identification; convolutional neural network (CNN); capsule network (CapsNet); multi-scale convolution-capsule network (MSCCN); image retrieval; Transformer; self-attention; knowledge distillation; hashing learning; Kuroshio Extension Observatory; sound speed profile; self-organizing map; circle chaotic map; Levy flight; nonlinear adaptive weight; tuna swarm optimization; quality of experience; human perception; electroencephalogram; crop disease leaf image segmentation (CDLIS); U-Net; dilated convolution; lightweight multi-scale dilated U-Net (LWMSDU-Net); crystal structure algorithm; golden sine algorithm; levy flight; engineering optimization problems; people counting; CSI; cross-modal learning network; graph neural network; propagation mechanism; data-driven method; gastrointestinal stromal tumor; semi-supervised learning; self-training; object detection