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IEEE Big Data - MMBD 2022 : IEEE Big Data 2022 Workshop on Multimodal Big Data (Virtually) | |||||||||||||||
Link: https://www.comstar-tech.org/workshops/workshop_2022_MMBD.html | |||||||||||||||
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Call For Papers | |||||||||||||||
Big Data technology has been one of the key engines driving the new industrial revolution. However, the majority of current Big Data research efforts have been devoted to single-modal data analysis, which leads to a huge gap in performance when algorithms are carried out separately. Although significant progress has been made, single-modal data is often insufficient to derive accurate and robust models in many applications.
Multimodal is the most general form for information representation and delivery in the real world. Using multimodal data is natural for humans to make accurate perceptions and decisions. In fact, our digital world is multimodal, combining different modalities of data such as text, audio, images, videos, animations, drawings, depth, 3D, biometrics, interactive content, etc. Multimodal data analytics algorithms often outperform single modal data analytics in many real-world problems. Multi-sensor information fusion has also been a topic of great interest in the industry nowadays. In particular, such companies working on automotive, drone vision, surveillance, or robotics have grown exponentially. They are attempting to automate processes by using a wide variety of control signals from various sources. With the rapid development of Big Data technology and its remarkable applications in many fields, multimodal Big Data is a timely topic. This workshop aims to generate momentum around this topic of growing interest and to encourage interdisciplinary interaction and collaboration between Natural Language Processing (NLP), computer vision, audio processing, machine learning, robotics, Human-Computer Interaction (HCI), cloud computing, Internet of Things (IoT), and geospatial computing communities. It serves as a forum to bring together active researchers and practitioners from academia and industry to share their recent advances in this promising area. ________________________________________ Topics This is an open call for papers, which solicits original contributions considering recent findings in theory, methodologies, and applications in the field of multimodal Big Data. The list of topics includes, but is not limited to: Multimodal representations multimodal data modeling and data fusion Multimodal learning, cross-modal learning Multimodal big data analytics, visualizaiton Multimodal big data infrastructure and management Multimodal scene understanding Multimodal perception and interaction Multimodal benchmark datasets and evaluations Multimodal information tracking, retrieval and identification Multimodal object detection, classification, recognition and segmentation Language, vision, audio, touch, etc. Multimodal AI in robotics (robotic vision, NLP in robotics, Human-Robot Interaction (HRI), etc.) Multimodal AI Safety (explainability, interpretability, trustworthiness, etc.) Multimodal Biometrics Multimodal applications (autonomous driving, cybersecurity, smart cities, intelligent transportation systems, industrial inspection, medical diagnosis, healthcare, social media, arts, etc.) ________________________________________ Important Dates Please visit the workshop website: https://www.comstar-tech.org/workshops/2024/workshop_2024_MMAI.html *Note that the main conference of IEEE Big Data 2024 will be in person but the MMAI workshop will be hosted both virtually and onsite. ________________________________________ Submission Please follow the web link to submit to IEEE Big Data 2024 paper submission site. Accepted papers will be published in the IEEE Big Data 2024 proceedings. |
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