Performance in HPC: Gnuplot & ARM map
Today’s workshop focused on exploring performance in a hybrid MPI/OpenMP application using tools such as Gnuplot and ARM Forge MAP.
Today’s workshop focused on exploring performance in a hybrid MPI/OpenMP application using tools such as Gnuplot and ARM Forge MAP.
Notes on the COMP3007 Machine Perception assignment and my reflection.
Short reflection on the year-long capstone computing project sequence, ISAD3000 and ISAD3001.
Notes on the COMP3009 Data Mining assignment and my reflection.
Quick reference notes for the COMP3007 AI ethics content.
3D perception extends 2D vision into depth and spatial structure. Instead of just asking “what is in this image?”, we ask: “what does the 3D world look like?”
Tracking extends perception from single images to video and dynamic scenes. Instead of just asking “what is this?”, we now ask: “where is it over time?”
Image segmentation divides an image into meaningful regions so that each region corresponds to a distinct object or part of an object.
Object detection goes beyond whole-image classification. It asks what objects are present and where they are, usually via bounding boxes.
Machine learning is the stage in the pipeline where features become decisions.
Feature extraction turns raw pixels into numerical descriptors that a machine can compare, match, and classify.
Notes from the COMP2007 Lecture, and online resources.
Similarity and distance measures are central to clustering, classification, and retrieval tasks.
Feature detection in computer vision, progressing from points and patches to edges and lines.
Notes from the COMP2007 Lecture, and online resources.
Data preparation is a critical step in transforming raw, messy real-world data into a format suitable for data mining algorithms. Poor preparation leads to u...
High-quality machine perception requires understanding image formation, anticipating imperfections, and applying suitable processing techniques.
Steps to remotely access Lab 314.232 machines for use in computing units.
Notes from the COMP2007 Lecture, and online resources.
Data mining bridges data and knowledge, combining cleaning, analysis, and modeling to deliver actionable insights in real-world applications.
Machine perception integrates sensing, preprocessing, feature extraction, and classification.
Short reflection of the COMP3010 Machine Learning unit.
Short reflection of the ICTE3002 Human Computer Interface unit.
Notes from the COMP3010 Machine Learning assignment.
Short reflection of the COMP3011 Web Application Frameworks unit.
Notes from the summary of COMP3011 Lecture 11, and online resources.
Notes from the summary of COMP3010 Lecture 11, labs, and online resources.
Notes from the COMP3011 Web App Frameworks assignment 3.
Notes from the summary of COMP3011 Lecture 8, 9, 10, and online resources.
Notes from the summary of COMP3010 Lecture 10, labs, and online resources.
Notes from the summary of COMP3010 Lecture 9, labs, and online resources.
Notes from the summary of COMP3010 Lecture 8, labs, and online resources.
Notes from the summary of COMP3010 Lecture 7, labs, and online resources.
Notes from the COMP3011 Web App Frameworks assignment 2.
Notes from the summary of COMP3011 Lecture 6, 7, and online resources.
Notes from the summary of COMP3010 Lecture 6, labs, and online resources.
Notes from the summary of COMP3011 Lecture 4, 5, and online resources.
Notes from the summary of COMP3010 Lecture 5, labs, and online resources.
Notes from the summary of COMP3010 Lecture 4, labs, and online resources.
Notes from the COMP3011 Web App Frameworks assignment 1.
Notes from the summary of COMP3011 Lecture 1, 2, 3 and online resources.
Notes from the summary of COMP3010 Lecture 3, labs, and online resources.
Notes from the summary of COMP3010 Lecture 2, labs, and online resources.
Notes from the summary of COMP3010 Lecture 1, labs, and online resources.
Notes from the summary of COMP2006 Lecture 1, labs, and online resources.
Short reflection of the COMP3010 Machine Learning unit.
Notes from the COMP3010 Machine Learning assignment.
Notes from the summary of COMP3010 Lecture 11, labs, and online resources.
Notes from the summary of COMP3010 Lecture 10, labs, and online resources.
Notes from the summary of COMP3010 Lecture 9, labs, and online resources.
Notes from the summary of COMP3010 Lecture 8, labs, and online resources.
Notes from the summary of COMP3010 Lecture 7, labs, and online resources.
Notes from the summary of COMP3010 Lecture 6, labs, and online resources.
Notes from the summary of COMP3010 Lecture 5, labs, and online resources.
Notes from the summary of COMP3010 Lecture 4, labs, and online resources.
Notes from the summary of COMP3010 Lecture 3, labs, and online resources.
Notes from the summary of COMP3010 Lecture 2, labs, and online resources.
Notes from the summary of COMP3010 Lecture 1, labs, and online resources.
Notes on the COMP3007 Machine Perception assignment and my reflection.
Quick reference notes for the COMP3007 AI ethics content.
3D perception extends 2D vision into depth and spatial structure. Instead of just asking “what is in this image?”, we ask: “what does the 3D world look like?”
Tracking extends perception from single images to video and dynamic scenes. Instead of just asking “what is this?”, we now ask: “where is it over time?”
Image segmentation divides an image into meaningful regions so that each region corresponds to a distinct object or part of an object.
Object detection goes beyond whole-image classification. It asks what objects are present and where they are, usually via bounding boxes.
Machine learning is the stage in the pipeline where features become decisions.
Feature extraction turns raw pixels into numerical descriptors that a machine can compare, match, and classify.
Feature detection in computer vision, progressing from points and patches to edges and lines.
High-quality machine perception requires understanding image formation, anticipating imperfections, and applying suitable processing techniques.
Machine perception integrates sensing, preprocessing, feature extraction, and classification.
Short reflection of the COMP3011 Web Application Frameworks unit.
Notes from the summary of COMP3011 Lecture 11, and online resources.
Notes from the COMP3011 Web App Frameworks assignment 3.
Notes from the summary of COMP3011 Lecture 8, 9, 10, and online resources.
Notes from the COMP3011 Web App Frameworks assignment 2.
Notes from the summary of COMP3011 Lecture 6, 7, and online resources.
Notes from the summary of COMP3011 Lecture 4, 5, and online resources.
Notes from the COMP3011 Web App Frameworks assignment 1.
Notes from the summary of COMP3011 Lecture 1, 2, 3 and online resources.
My short reflection after my first internship.
Reflection on Google Cloud Security Summit Asia Pacific 2025
These are my thoughts these days.
A short reflection on Webinar: How to Get a Job in Engineering.
A short reflection on sem 2 2025 vollies in July.
The Discovery of an Interesting Book: The Elements of Differentiable Programming
These are my thoughts these days.
Welcome to my blog!
A Quick Note on Attention, Transformers, and the New Linear Models.
A quick reflection of the AARP site visit on the 9th Wed, July.
A reflection on completing my AWS Certified AI Practitioner (AIF-CO1).
A short reflection of Completion of Microsoft AI Skills for Students program.
On this day, I completed the AWSome Day Online Conference and deepened my understanding of AWS cloud technologies. The three‑hour workshop highlighted the im...
What is MCP? Model Context Protocol (MCP) is an open standard that allows AI models to connect to external tools and data sources seamlessly—without the need...
Insights from Geoffrey Hinton on the Future of AI
Notes on the COMP3009 Data Mining assignment and my reflection.
Similarity and distance measures are central to clustering, classification, and retrieval tasks.
Data preparation is a critical step in transforming raw, messy real-world data into a format suitable for data mining algorithms. Poor preparation leads to u...
Data mining bridges data and knowledge, combining cleaning, analysis, and modeling to deliver actionable insights in real-world applications.
Notes from the COMP2007 Lecture, and online resources.
Notes from the COMP2007 Lecture, and online resources.
Notes from the COMP2007 Lecture, and online resources.
Notes from the summary of COMP2006 Lecture 1, labs, and online resources.
Short reflection of the ICTE3002 Human Computer Interface unit.
Short reflection on the year-long capstone computing project sequence, ISAD3000 and ISAD3001.
Quick Differentiation Rules
Today’s workshop focused on exploring performance in a hybrid MPI/OpenMP application using tools such as Gnuplot and ARM Forge MAP.