1. Introduction “If you can detect lines, you can understand structure.” That’s something I learned early when working with computer vision. Whether you’re building a self-driving car or automating document analysis, detecting lines is often the first step toward making sense of an image. So, what exactly is line detection? In simple terms, it’s identifying … Read more
OpenCV Line Detection – A Practical Guide Read More »
I. Introduction “Text is everywhere—on street signs, product labels, scanned documents, you name it. But making a machine accurately detect and extract it? That’s a whole different challenge.” Over the years, I’ve worked with multiple text detection methods, from traditional computer vision techniques to deep learning-based approaches. Some work like magic on clean documents, while … Read more
Text Detection with OpenCV: A Practical Guide Read More »
I. Introduction “A good tool in the wrong hands is useless. A great tool in the right hands? Game-changing.” Object recognition is one of those things that seems deceptively simple—until you actually start implementing it. When I first started working with OpenCV for object recognition, I thought, How hard can it be? Just feed in … Read more
Object Recognition with OpenCV: A Practical Guide Read More »
1. Introduction (Brief & Straight to the Point) “Theory is great, but if you can’t build something real with it, what’s the point?” I’ve worked on countless computer vision projects, and if there’s one thing I’ve learned, it’s this: practical implementation beats theoretical knowledge every single time. You can read all the papers you want, … Read more
Computer Vision Project Ideas With Code Read More »
I. Introduction “Not all data is created equal. And in machine learning, this imbalance can cost you—big time.” If you’ve worked with real-world datasets, you already know the struggle. Most classification problems aren’t neatly balanced, where each class has an equal number of samples. In reality, some categories are severely underrepresented. Think about fraud detection—99.9% … Read more
Implementing Focal Loss in PyTorch for Class Imbalance Read More »
1. Introduction “If you torture the data long enough, it will confess to anything.” – Ronald Coase I’ve learned over the years that raw data never tells the full story upfront. That’s where Exploratory Data Analysis (EDA) comes in—it’s like detective work for data scientists. Before jumping into complex machine learning models, you need to … Read more
Exploratory Data Analysis Projects with Python Code: From Beginner to Advanced Read More »
1. Introduction “If you torture the data long enough, it will confess to anything.” – Ronald Coase I’ve always believed that data has a story to tell, but it won’t reveal its secrets unless you ask the right questions. That’s where Exploratory Data Analysis (EDA) comes in. If you’ve ever worked with raw data, you … Read more
Exploratory Data Analysis in R: A Step-by-Step Guide with Code Examples Read More »
I. Introduction “In God we trust. All others must bring data.” – W. Edwards Deming If there’s one thing I’ve learned in my years working with machine learning models, it’s this: your model is only as good as the decisions it makes. And when it comes to decision-making in machine learning, decision trees are one … Read more
Understanding Information Gain in Decision Trees: A Complete Guide Read More »
1. Introduction “Your eyes say more than your words ever could.” – That’s not just a poetic thought; it’s a reality that technology is now learning to interpret. Eye tracking has fascinated me for years, especially with its applications in AR/VR, gaming, marketing, and even assistive technology. The idea that a system can analyze where … Read more
OpenCV Eye Tracking: Step-By-Step With Code Read More »
I. Introduction “If you do what you’ve always done, you’ll get what you’ve always gotten.” – Tony Robbins. When I first started working with convolutional neural networks (CNNs) for image classification, I was blown away by their ability to detect edges, textures, and patterns. But as I moved on to more complex datasets—think medical imaging … Read more
Attention Mechanism for Image Classification Read More »
