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Found 3 papers, 2 papers with code
Weakly Supervised Attention-based Models Using Activation Maps for Citrus Mite and Insect Pest Classification
Despite the integrated pest mechanical aspect, only a few works on automatic classification have handled images with orange mite characteristics, which means tiny and noisy regions of interest.
Weakly Supervised Learning Guided by Activation Mapping Applied to a Novel Citrus Pest Benchmark
Pests and diseases are relevant factors for production losses in agriculture and, therefore, promote a huge investment in the prevention and detection of its causative agents.
Combating the Elsagate phenomenon: Deep learning architectures for disturbing cartoons
As the first to explore disturbing content in cartoons, we proceed from the most recent pornography detection literature applying deep convolutional neural networks combined with static and motion information of the video.
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