pretrained-spatial-CNN
Spatial-CNN for lane detection in MATLAB.
AI summary
Lane detector
An implementation of a deep learning-based lane detection model in MATLAB using a pre-trained Spatial-CNN architecture.
- stars
- 24
- forks
- 12
- watching
- 5
Similar projects
Found by comparing what the projects do, not just their names.
Road detector
A MATLAB implementation of a deep learning-based road boundary detection system using a pre-trained RESA model.
Object detector
Provides pre-trained and customizable object detection capabilities using an efficient neural network architecture
Object Detector
Pretrained YOLO object detection networks for real-time performance with good detection quality in MATLAB
Object Detector
Provides pre-trained YOLO object detection networks in MATLAB for real-time performance with good detection quality.
Object Detector
Pretrained deep learning object detection model for image analysis in MATLAB
Object Detector
Provides pre-trained deep learning models for object detection in point clouds using complex YOLOv4 architecture
Lane detector
This is a machine learning project that uses deep learning to detect lane lines on road images
Object detector
A Matlab implementation of simultaneous object detection and segmentation using deep learning techniques.
OFDM detector
A MATLAB implementation demonstrating the power of deep learning in signal detection and channel estimation for OFDM systems
EEG classifier
Develops and trains a deep neural network to classify EEG signals as normal or abnormal
Tracker library
A Matlab implementation of a real-time tracker using convolutional neural networks for object tracking in visual environments.
Digit detector
Automates digit recognition in images of seven segment displays
Vehicle Detector
A Matlab project for vehicle detection and recognition using deep learning techniques.
CNN library
A Matlab implementation of a 2D Convolutional Neural Network for educational purposes
Pedestrian detector
Matlab implementation of an object detection algorithm for pedestrians using a Histogram of Oriented Gradients descriptor
