Sep 27, 2021 � We explore the feasibility of using crowdsourcing to acquire reliable soft-target labels and evaluate an emotion detection classifier trained with these labels.

Jan 10, 2021 � We explore the use of crowdsourcing to acquire reliable soft-target labels and evaluate an emotion detection classifier trained with these labels.

Sep 12, 2021 � We then train two versions of a ResNet-152 neural network on soft-target CAFE labels using the original 100 annotations provided with the�...

We explore the use of crowdsourcing to acquire reliable soft-target labels and evaluate an emotion detection classifier trained with these labels. We center our�...

Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels ... training with ambiguous emotional utterances for DNN-based speech emotion�...

"Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels." Cognitive Computation 13, no. 5 (2021): 1363-1373. Kim, Kuno, Megumi Sano�...

We first acquire crowdsourced labels for 207 emotions from CAFE and demonstrate that the consensus labels from the crowd tend to match the consensus from the�...

Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels � no code implementations • 10 Jan 2021 • Peter Washington, Onur Cezmi Mutlu�...

In this paper we study how emotion labels for images can be crowdsourced and uncover limitations of the approach commonly used to gather training data today,�...

"Training Affective. Computer Vision Models by Crowdsourcing Soft-Target Labels." Cognitive Computation 13, no. 5 (2021): 1363-1373. 51. Washington, Peter�...