Real Time Audio-Visual Sensing and Sense Making

Overview

Reference No	TGS-2020001514
Part of	-
Duration	4 days
Course Time	9.00am - 5.00pm
Enquiry	Please email ask-iss@nus.edu.sg for more details

Curious about how machines can see and hear the world around us, transforming perceptions into actions?

This course is designed for professionals seeking to leverage audio and video analytics in their operations. This course offers a deep dive into the core technologies that enable machines to interpret audio-visual data, providing actionable intelligence in real-time to enhance business intelligence and operational efficiency.

Discover how these systems can empower robots to navigate autonomously and interact with their environment, or how they can be applied to human activity interpretation, real-time crowd surveillance, healthcare monitoring, and customer emotion recognition in retail. Through a blend of theoretical knowledge and hands-on workshop sessions, participants will gain practical skills to process, integrate, interpret, and respond to audio-visual data.

Course Content

Real-Time Video Sensing: Modelling and processing.
Real-Time Video Analytics: Motion analysis and object tracking (e.g., DeepSORT); video analytics using deep learning (e.g., C3D, Two-stream).
Real-Time Audio and Speech Analytics: Through the utilisation of deep learning (e.g., wav2vec, conformers).
Practicality: Practical case studies and workshops

This course is part of the Artificial Intelligence and Graduate Certificate in Intelligent Sensing Systems Series offered by NUS-ISS.

Key Takeaways

Recognise the requirements and potential of real-time audio-visual sensing technologies across diverse industrial applications.
Design and implement audio-visual sense-making methods tailored for industrial scenarios using machine learning.
Evaluate the effectiveness and impact of various real-time audio-visual sense-making technologies.
Critically analyse, evaluate, and synthesise information to address complex audio-visual sensing challenges.

Who Should Attend

Software Developers and Engineers tasked with creating sophisticated audio-visual data sensing systems.
Data Scientists who specialise in the analysis of audio and visual data.
System Architects who integrate audio and visual data analytics into comprehensive solutions.
Product Managers/Owners and Consultants seeking expertise in audio and visual data sense-making to design, manage, and assess system applications.

Prerequisites

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).

Course Logistics

No Printed Materials: Course materials are accessed digitally. Do kindly note that no printed copies of course materials will be issued.
Device Requirements: Bring an internet-enabled device (laptop, tablet, etc) with power chargers to access and download course materials.

If you are bringing a laptop, kindly refer to the table below for the recommended tech specs:

	Minimum	Recommended
Operating Systems	• Windows 7 above • Mac OS	Laptop running the latest version of either Windows or Mac OS
System Type	32-bit	64-bit
Memory	8 GB RAM	16+ GB RAM
Hard Drive	256 GB disk size
Others	• An internet connection – broadband wired or wireless • Installation permissions (non-company laptops) • Keyboard • Mouse/Trackpad • Display • Power adapter (laptop battery might run out)	DirectX 10 graphics card for graphics hardware acceleration

Fees & Subsidies

Certificate

Certificate of Completion
Participants have to meet a minimum attendance rate of 75% and are required to pass the assessment to be issued a Certificate of Completion.

Join Us

Preparing for Your Course

NUS-ISS Course Registration Terms and Conditions

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NUS-ISS and Learner’s Commitment and Responsibilities

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WIFI Access

WIFI access will be made available to participants.

Venue

NUS-ISS
25 Heng Mui Keng Terrace
Singapore 119615

Click HERE for directions to NUS-ISS

In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

Course Confirmation

All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

General Enquiry

Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.

Course Resources

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