Isset in PHP Function With Examples
The isset in PHP is a built-in PHP function that checks if a variable is set or not. It simply means that it should be declared and not be NULL. …
PHP Filesize with Program Example
In this tutorial, we will discuss how to get the file size using PHP. To get the file size we will need the file size function. Also, we will know …
PHP pathinfo Function With Examples
The PHP pathinfo is a built-in PHP function which used to return information about the file path. In this article, we will talk about pathinfo PHP function in a detailed explanation as …
Excel Match Function With Examples and How to Use
This tutorial will elaborate the Excel Match function along with examples and how to use it. Moreover, this will helps in your skill in analyzing and lookup and matching data. …
STR Contains PHP Function With Examples
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PHP __call Magic Method With Example
The PHP __call is a method which invoked automatically when there is an inaccessible or non-existing method were called. In this article, we will talk about PHP __call() function in …
Excel Index Function Example, Formula, How to Use
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PHP Usort Function With Examples
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PHP array_filter function With Examples
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How PHP Multiline String With Examples
In PHP, the multiline string is very easy they can be written in three different ways, such as with the use of escape sequences, Nowdoc and Heredoc syntax and concatenation …
Excel Conditional Formatting Ways to Apply and Examples
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PHP Get Current Year with Example Code
In this tutorial, we will discuss on how to get current year in PHP. The Date function is an inbuilt function that is used to format the timestamp. There are …
PHP basename Function With Examples
The PHP basename is a function which returns the filename of a file path directory. In this article, we will talk about PHP basename in a detailed explanation as well …
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.