Modeling human attention by learning from large amount of emotional images
Recent resurgence of neural networks in computer vision have resulted in tremendous improvements in saliency prediction, eventually, saturating some saliency metrics. This leads researchers to devise higher-level concepts in images in order to match the key image regions attended to by human observe...
Saved in:
Main Author: | Cordel, MacArio O. |
---|---|
Format: | text |
Published: |
Animo Repository
2019
|
Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2018 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
Similar Items
-
End-to-End Speech Emotion Recognition Using Multi-Scale Convolution Networks
by: Sivanagaraja, Tatinati, et al.
Published: (2018) -
Emotion recognition in spontaneous Filipino speech using machine learning classification
by: Ong, Arlyn Verina L.
Published: (2012) -
IMPROVING ATTENTION-BASED DEEP LEARNING MODELS WITH LOCALITY
by: JIANG ZIHANG
Published: (2023) -
Effects of music and speech on the neural correlates of emotion and attention
by: NICOLAS RENE ESCOFFIER
Published: (2013) -
Emotion-aware human attention prediction
by: Cordel, MacArio O., et al.
Published: (2019)