Hi, I'm Yeo Kheong Jie

Computer Engineering Student & Digital Innovator

I transform complex problems into elegant solutions through code, creativity, and continuous learning. Currently bridging the gap between Deep Learning and industrial agricultural applications.

View My Work

About Me

Getting to know the person behind the code

Yeo Kheong Jie Profile

Passionate Computer Engineering Student

My journey is driven by a desire to create meaningful digital experiences. From optimizing IoT micro-climates to developing CNN architectures for automated grading, I believe technology should solve real-world challenges.

Currently studying at UTeM (FTKEK), I focus on AI in medical imaging, IoT networks, and Python automation. I am committed to continuous learning and industrial application.

Technical Skills

Python
MATLAB
TensorFlow
C++ / Java
Arduino
Git

Passion for Excellence

What drives my engineering philosophy

đź’ˇ

Problem Solving

I thrive on finding innovative solutions to complex technical hurdles.

🤝

Collaboration

I believe diverse perspectives lead to superior, more robust engineering designs.

🚀

Continuous Learning

Commited to staying current with the rapid evolution of technology and tools.

Research & Projects

Academic contributions and ongoing investigations

âś“ Published Research

IoT-Based Greenhouse Monitoring

Implemented a smart system using DHT11 and MQ135 sensors to mitigate industrial pollution impacts on agriculture.

Read Paper →
⏳ Ongoing (PSM1)

Deep Learning-Based Oil Palm Ripeness Classification

Designing a CNN-based system to replace manual grading with high-precision detection (Unripe, Under-ripe, Ripe, Over-ripe) to optimize OER.

View Proposal PDF →

Padlet Journey

Technical Padlet milestones in Digital Image Processing (BERR4723)

Intro
Section 02

Introduction

Foundation setup for the portfolio journey at UTeM.

Acquisition
Section 03

Image Acquisition

Studied Images as 2D functions f(x,y) and vision goals.

Sampling
Section 04

Fundamentals

Analyzed Spatial vs. Intensity Resolution; Sampling & Quantization.

Enhancement
Section 05

Enhancement

Applied Histogram Equalization and Spatial Filters for noise reduction.

Restoration
Section 06

Restoration

Applied Wiener Filtering using the Degradation Model.

Reflection
Section 07

Reflection

Insight: The leap from grayscale to color and multi-stage engineering workflows.

Geometric Trans
Section 08

Geometric Trans.

Applied Scaling, Rotation, and Translation with Bilinear Interpolation.

Color
Section 09

Color Processing

Leveraged HSI color space for robust segmentation in varying light.

Wavelet Trans
Section 10

Wavelet Trans.

Multi-resolution analysis. Used Wavelets to isolate localized edges/textures.

Compression
Section 11

Compression

Evaluated Lossy vs. Lossless methods using PSNR metrics.

Misc
Section 12

Miscellaneous

Group project artifacts, lab reports, and peer interactions.