Extracting (ranked) softmax values for each validation image
4 次查看(过去 30 天)
显示 更早的评论
Hi everyone,
I trained a model (fine tuning) to classify 10 types of images. I was just wondering if there was a simple way to return, say, a matrix containing all validation images (with their respective names/labels) and their predictive scores (classification confidence) ?
Thank you !
Best regards.
0 个评论
采纳的回答
Srivardhan Gadila
2020-8-23
Use the activations function to get the output of softmaxLayer & use the max function to get the maximum of all scores i.e., score of the predicted class. Also I think you can use the same Name-Value Pair Arguments & Syntax used for predict function. You can refer to Visualize Activations of a Convolutional Neural Network for more examples on the usage of activations function.
0 个评论
更多回答(0 个)
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!