Li-Ming Chen
Self-Reported Frequency and Perceived Severity of Being Bullied Among Elementary School Students
The Journal of school health
propose technique producing visual explanations decisions large class convolutional neural network cnnbased models making transparent explainable approachgradientweighted class activation mapping gradcam uses gradients target concept say dog classification network sequence words captioning network flowing final convolutional layer produce coarse localization map highlighting important regions image predicting concept unlike previous approaches gradcam applicable wide variety cnn modelfamilies 1 cnns fullyconnected layers egvgg 2 cnns used structured outputs egcaptioning 3 cnns used tasks multimodal inputs egvisual question answering reinforcement learning without architectural changes retraining combine gradcam existing finegrained visualizations create highresolution classdiscriminative visualization guided gradcam apply image classification image captioning visual question answering vqa models including resnetbased architectures context image classification models visualizations lend insights failure modes models showing seemingly unreasonable predictions reasonable explanations b outperform previous methods ilsvrc15 weaklysupervised localization task c robust adversarial perturbations faithful underlying model e help achieve model generalization identifying dataset bias image captioning vqa visualizations show even nonattention based models learn localize discriminative regions input image devise way identify important neurons gradcam combine neuron names bau et al computer vision pattern recognition 2017 provide textual explanations model decisions finally design conduct human studies measure gradcam explanations help users establish appropriate trust predictions deep networks show gradcam helps untrained users successfully discern stronger deep network weaker one even make identical predictions code available httpsgithubcomramprsgradcam along demo cloudcv agrawal et al mobile cloud visual media computing pp 265290 springer 2015 httpgradcamcloudcvorg video httpyoutubecojub9izk6e