Real Time Audio-Visual Sensing and Sense Making

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

• 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.

Fees & Subsidies

Certificate

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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

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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.