AS-0167/D3-CNN-2
A simplified and improved academic project implementing a CNN from scratch using NumPy to detect driver distractions. D3-CNN-2 achieves ~86% test accuracy in just 11 epochs, outperforming the original model with fewer layers. Includes a Streamlit-based frontend for real-time image/video testing — all without using PyTorch or TensorFlow.
No commits in the last 6 months.
Stars
2
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
May 21, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/AS-0167/D3-CNN-2"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ndrplz/dreyeve
[TPAMI 2018] Predicting the Driver’s Focus of Attention: the DR(eye)VE Project. A deep neural...
ykotseruba/attention_and_driving
A curated list of peer-reviewed papers on theoretical and practical aspects of drivers'...
ciglenecki/eeg-driver-fatigue-detection
🧠 + 🚗 Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system
Pratham-mehta/Real-time-Driver-Drowsiness-Detection-System-Using-Deep-Learning
CS-GY 6953 Deep Learning Major Project
ivineetm007/drunk-detection
This repository contains the source code for the paper Dataset of Perceived Intoxicated Faces...