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{ {
"index":4, "index":4,
"title":"Pixel Attribution", "title":"Pixel Attribution",
"paper":"Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps", "paper":"Efficient Saliency Maps for Explainable AI",
"chapter":"10.2", "chapter":"10.2",
"by": "Simonyan, Vedaldi, et al.", "by": "Mundhenk, Chen, et al.",
"when": "2013", "when": "2019",
"who": "Simon Klüttermann", "who": "Simon Klüttermann",
"mail": "simon.kluettermann@cs.uni-dortmund.de", "mail": "simon.kluettermann@cs.uni-dortmund.de",
"note1":"Different parts of an image have different effect/importance on the classification of an image", "note1":"Different parts of an image have different effect/importance on the classification of an image",
"note2":"{null}", "note2":"Programming task: Generate one Saliency Map yourself!",
"ext": "jpeg" "ext": "jpeg"
} }

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\frametitle{Topic 4: Pixel Attribution} \frametitle{Topic 4: Pixel Attribution}
\Large \textbf{Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps} (Simonyan, Vedaldi, et al., 2013)\\ \Large \textbf{Efficient Saliency Maps for Explainable AI} (Mundhenk, Chen, et al., 2019)\\
\LARGE \textbf{Chapter:} 10.2 \textbf{Supervisor:} Simon Klüttermann (simon.kluettermann@cs.uni-dortmund.de)\\ \LARGE \textbf{Chapter:} 10.2 \textbf{Supervisor:} Simon Klüttermann (simon.kluettermann@cs.uni-dortmund.de)\\
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\item Programming task: Generate one Saliency Map yourself!
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