Jan 12, 2023 · This book is the result of a seminar in which we reviewed multimodal approaches and attempted to create a solid overview of the field, starting with the current state-of-the-art approaches …

Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.

In this work, we propose a novel application of deep networks to learn features over multiple modalities. We present a series of tasks for multimodal learning and show how to train deep networks that learn …

Multimodal deep learning is a subfield of machine learning where deep neural networks learn from multiple modalities of data (e.g., images, text, audio) simultaneously, instead of just one.

Multimodal deep learning has become a primary methodological framework in artificial intelligence, allowing models to learn from (and reason over) many different types of data, such as text, images, …

Jan 11, 2023 · In this seminar, we reviewed these approaches and attempted to create a solid overview of the field, starting with the current state-of-the-art approaches in the two subfields of Deep Learning …

This Collection aims to bring together cutting-edge research, novel architectures, benchmark studies, and practical applications in deep learning for multimodal data processing.

Jul 23, 2024 · Multimodal deep learning plays a pivotal role in supporting the processing and learning of diverse data types within the realm of artificial intelligence generated content (AIGC).

Multimodal Deep Learning is a machine learning subfield that aims to train AI models to process and find relationships between different types of data (modalities)—typically, images, video, audio, and text.

Jul 8, 2025 · Multimodal deep learning has become a primary methodological framework in artificial intelligence, allowing models to learn from (and reason over) many different types of data, such as …