Generating representations of video data is of key importance in advancing the field of machine perception.
With the growing adoption of short-form video by social media platforms, reducing the spread of misinformation through video posts has become a critical challenge for social media providers.
For White students, different types of educational support were important in predicting academic achievement, while for non-White students, different types of emotional support were important in predicting academic achievement.
We present a new publicly available dataset with the goal of advancing multi-modality learning by offering vision and language data within the same context.
Learning from demonstrations is a popular tool for accelerating and reducing the exploration requirements of reinforcement learning.
Traditionally artificial neural networks (ANNs) are trained by minimizing the cross-entropy between a provided groundtruth delta distribution (encoded as one-hot vector) and the ANN's predictive softmax distribution.
Evaluating the return on ad spend (ROAS), the causal effect of advertising on sales, is critical to advertisers for understanding the performance of their existing marketing strategy as well as how to improve and optimize it.
In fact, the Internet is a Word Wild Web of facial images with expressions.
Despite efforts made in developing various methods for FER, existing approaches traditionally lack generalizability when applied to unseen images or those that are captured in wild setting.