Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …

Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …

Multimodal deep learning systems that employ multiple modalities like text, image, audio,
video, etc., are showing better performance than individual modalities (ie, unimodal) …

Machine learning techniques are increasingly gaining attention due to their widespread use
in various disciplines across academia and industry. Despite their tremendous success …

Automating decision systems has led to hidden biases in the use of artificial intelligence (AI).
Consequently, explaining these decisions and identifying responsibilities has become a …

There are demographic biases present in current facial recognition (FR) models. To
measure these biases across different ethnic and gender subgroups, we introduce our …

Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents capable of understanding, reasoning, and learning through integrating …

Building multisensory AI systems that learn from multiple sensory inputs such as text,
speech, video, real-world sensors, wearable devices, and medical data holds great promise …

The recruitment process is crucial to an organization's ability to position itself for success,
from finding qualified and well-fitting job candidates to impacting its output and culture …

Several studies previously demonstrated that underrepresented minority (URM) groups
often struggle to access highqualified jobs. At the same time, a wide range of researches …