Real Time Audio-Visual Sensing and Sense Making
About This Course
This course is designed for professionals seeking to harness the power of computer vision and audio analytics technology to analyze and interpret audio and vision data. It offers an in-depth exploration of the core technologies and systems that enable machines to interpret audio and vision data, providing actionable intelligence in real-time to enhance business intelligence and operational efficiency.
The skills and knowledge gained from this course can be applied in various industries, including autonomous navigation, healthcare diagnostics, and retail customer behavior analysis, to enhance operational efficiency and innovation. Learners can also implement audio-visual sensing technologies in security, smart cities, manufacturing, and media to improve safety, manage resources, and optimize processes.
What You'll Learn
Identify the needs of real-time audio-visual sensing technology and sense-making methods in various industrial applications.
Design and apply audio-visual sense-making methods to industrial use cases, including audio sensing, video analytics, and state-of-the-art machine learning-based sense-making approaches.
Assess the performance and usefulness of various real-time audio-visual sense-making technologies.
Apply critical analysis, evaluation, and synthesis to a wide range of audio-visual sensing problems.
Analyze, articulate, and apply their new skills in their work and within their teams and organizations.
Entry Requirements
Participants should have intermediate skills in Python programming (e.g. Numpy, Pandas), and/or OpenCV programming (e.g. able to apply filtering and transformation on the image).
Experiences in using Jupyter Notebooks, Google Colab and well-versed in package installation.
Participants must have an intermediate knowledge of computer vision at the level of Vision Systems (e.g. image processing, image classification and object detection using deep learning).