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Save yang-zhang/ec071ae4775c2125595fd80f40efb0d6 to your computer and use it in GitHub Desktop.
thanks for sharing....but, is that really a multi-task model? what's the architecture of the network really? Does it have a classical MTL structure which including a backbone and multi-head? or just only use resnet50.....sorry, could you explanin a little bit more...?
It's a classical multi-task learning architecture, which uses hard parameters sharing method. For example,
$loss_{total} = \lambda_{age} * loss_{age} + \lambda_{gender} * loss_{gender}$
@icmpnorequest
as far as i know, only calculating the loss together doesn't make the model to have a multi-task structure, you are doing the multi-objective learning without a multi-task model structure, right?
if the model structure is really using the classical multi-task structure as you said, could you tell me which paper/webpage you refer to?
thanks.
$loss_{total} = \lambda_{age} * loss_{age} + \lambda_{gender} * loss_{gender}$ @icmpnorequest
as far as i know, only calculating the loss together doesn't make the model to have a multi-task structure, you are doing the multi-objective learning without a multi-task model structure, right?
if the model structure is really using the classical multi-task structure as you said, could you tell me which paper/webpage you refer to?
thanks.
Maybe you could refer to the paper [19 CVPR] Multimodal Age and Gender Classification Using Ear and Profile Face Images
Hi , i have errors in imageCLassificationDataset ( function not defined) and ImageDatabunch ( flase argument for size , non existent ). Is there anyway to correct them ?
If anyone else is facing issues when running this example I have run through hell to build a multitask model. I hope I save some people time with this ready to run on Colab example https://github.com/apssouza22/cnn-for-devs/blob/master/i-multitask-model.ipynb
thanks for sharing....but, is that really a multi-task model? what's the architecture of the network really? Does it have a classical MTL structure which including a backbone and multi-head? or just only use resnet50.....sorry, could you explanin a little bit more...?