What is the Difference Between Git vs GitHub
WHAT IS THE DIFFERENCE BETWEEN GIT VS GITHUB – “Git” and “GitHub” are powerful innovations in software development that come to mind when mentioned. In this article, we’ll explore these …
What is Math.abs() method and How to use it in JavaScript?
Explore the powerful math.abs() method, also known as the Absolute Value function, in JavaScript. This article will walk you through its definition, usage, and examples of this fundamental mathematical concept. So to have …
The Role of Outsourced IT Support in Business
THE ROLE OF OUTSOURCED IT SUPPORT IN BUSINESS – In today’s fast-paced and technologically-driven business are constantly faced with the challenge of efficiently managing their IT infrastructure. This introduction, we …
Complete Guide in Javascript Adding Dates
Dates play a crucial role in web development, from displaying the current date and time to handling complex date calculations. This article delves into a range of approaches and strategies …
What is JavaScript async foreach? How To Use It?
In this article, we will delve into the world of JavaScript Async Foreach, exploring its benefits, use cases, and best practices. We will demonstrate how this method can optimize your …
How to change button text JavaScript?
In this article, you are going to learn to change the button text in JavaScript. Also, we will discuss the different methods to get this functionality with JavaScript, offering you …
How to Create an Accordion in JavaScript?
In this article, we will show you how to create an interactive accordion element in JavaScript with this comprehensive guide. We’ll start with the fundamentals and gradually move on to more advanced …
How to Calculate in Javascript Average? | 3 Methods
One of the essential concepts in data handling is the “average.” Whether you’re a beginner or an experienced developer, understanding the intricacies of calculating averages in JavaScript is crucial. In …
How to use MD5 hashes in JavaScript
In this article, you are going learn to use the MD5 hashes in JavaScript. The MD5 hash function was originally created as a secure cryptographic algorithm to authenticate digital signatures. …
How to Add an ID to an Element in JavaScript? Effective Methods
Are you having a hard time with how to add an ID to an Element using JavaScript? Well, this article is indeed for you! In this article, you’ll be able …
What is Rhino JavaScript?
In this article, we will discuss the JavaScript rhino, providing an example of codes, understanding, and expert knowledge to help you unleash the full ability of Rhino in your projects. …
How to add key-value pair to an object in JavaScript?
In this article, we are going to show you how to add a key to an object in JavaScript with this comprehensive guide. Get the solutions here and use them …
How To Change In Javascript Background Color?
JavaScript is a powerful programming language that has revolutionized web development. One of its key features is the ability to control the appearance of web elements dynamically. In this article, …
Frequently Asked Questions
Are these deep learning projects free for capstone and thesis use?
Yes. All deep learning projects on this hub are free to download, modify, and submit. No attribution required for academic use. Most are MIT-licensed or include source-code packs with sample datasets and pretrained model weights.
What deep learning frameworks do I need installed?
Most projects use OpenCV (cv2) for video capture and image preprocessing, plus one of: TensorFlow / Keras (Caffe model loading via cv2.dnn, custom CNN training), PyTorch (research-style models, YOLO v5+, transformers), or MediaPipe (Google's optimized face/hand/pose detectors). Install with pip install opencv-python tensorflow keras torch torchvision mediapipe numpy. Python 3.10, 3.11, or 3.12 recommended (avoid 3.13 until all wheels catch up).
Do I need a GPU to run these deep learning projects?
For inference (running a pretrained model on your webcam): no, CPU runs at 15-30 FPS for most computer-vision tasks. For training a custom model on your own dataset: GPU strongly recommended (CPU works but is slow). Free GPU options: Google Colab Free (12-hour sessions, sufficient for most BSIT capstones), Kaggle Notebooks Free (30-hour weekly quota), Paperspace Free tier. No need to buy a $1000+ GPU just for a capstone defense.
Deep learning vs classical machine learning, which should I pick for my capstone?
Pick deep learning when your inputs are unstructured (images, audio, video, text) and you have 10,000+ training samples. Pick classical ML (random forest, SVM, logistic regression) for tabular data, small datasets (under 1,000 rows), or when you need explainable predictions for the panel. Many capstones combine both: deep learning for feature extraction (face embedding via FaceNet) plus classical ML on top (SVM classifier for identity matching).
Why is my OpenCV deep learning model running at 2 FPS?
Three usual causes: (1) Resolution too high, resize frames to 640x480 or 320x240 before inference. (2) Wrong cv2.dnn backend, set net.setPreferableBackend(cv2.dnn.DNN_BACKEND_OPENCV) and net.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU). (3) Heavy model on weak hardware, swap YOLO v5 for MobileNet-SSD or use Haar cascades for simple face/eye detection. Also close other applications and disable laptop battery-save throttling.
Can I extend a single OpenCV demo into a full BSIT capstone?
Yes, and you should. A standalone webcam demo (face detection alone) is too narrow for capstone scope. Wrap it in a real system: face recognition becomes Real-Time Attendance System with PHP/MySQL dashboard, object detection becomes Smart CCTV Alert System with email notifications, drowsiness detection becomes Driver Monitoring System for fleet vehicles. Add user accounts, database logging, simple admin UI, and write Chapters 1-5 manuscript to satisfy panel requirements.
How often is this deep learning projects list updated?
New deep learning projects are added periodically as we receive student requests and new models become OpenCV-compatible. Last refreshed June 2026 with 19 vision-focused projects covering face recognition, object detection, traffic-sign classification, OCR, and more.