English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper presents an audiovisual-based emotion recognition hybrid network.While most of the previous work focuses either on using deep models orhand-engineered features extracted from images, we explore multiple deep modelsbuilt on both images and audio signals. Specifically, in addition toconvolutional neural networks (CNN) and recurrent neutral networks (RNN)trained on facial images, the hybrid network also contains one SVM classifiertrained on holistic acoustic feature vectors, one long short-term memorynetwork (LSTM) trained on short-term feature sequences extracted from segmentedaudio clips, and one Inception(v2)-LSTM network trained on image-like maps,which are built based on short-term acoustic feature sequences. Experimentalresults show that the proposed hybrid network outperforms the baseline methodby a large margin.

Audio-video Emotion Recognition in the Wild using Deep Hybrid Networks