https://www.selleckchem.com/pr....oducts/2-3-cgamp.htm
For this reason, the attention mechanism is capable of suppressing the temporal redundancy and highlighting the discriminative frames. Lastly, the framework is assessed by using HMDB51 and UCF101 datasets. As revealed from the experimentally achieved results, our ATEN with BIMM gains 94.5% and 70.6% accuracy, respectively, which outperforms a number of existing methods on both datasets.This article proposes an innovative RGBD saliency model, that is, attention-guided feature integration network, which can extract and fuse features and
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