kirilcvetkov92/Semantic-Segmentation-BiSeNet

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Created over 5 years ago
Updated over 2 years ago

kirilcvetkov92/Semantic-Segmentation-BiSeNet

kirilcvetkov92

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Keras BiseNet architecture implementation

Path-planning

Path planning implemented with behavior trees

Vehicle-Detection

Vehicle detection implemented with you Only Look Once. It's an object detector that uses features learned by a deep convolutional neural network to detect an object.

Jupyter Notebook

Instagram-Crawler

Scraping instagram profile information

Lane-Detection

Self driving car Lane detection

Traffic-sign-classifier

In this project, deep neural networks and convolutional neural networks are used to classify traffic signs. A model is trained so it can decode traffic signs from natural images by using the German Traffic Sign Dataset. After the model is trained, the model is tested on new images of traffic signs that are found on the web

Self-Driving-Car-Behavior-Deep-Learning

End-to-End Deep Learning and Behavior cloning for Self-Driving Cars

FCN-Semantic-Segmentation

Tensorflow impementation of Fully Convolutional Network (FCN) for Image Segmentation on both Kitti/Cityscapes dataset

Jupyter Notebook

Advanced-Lane-Detection

Software pipeline to identify the lane boundaries in a video from a front-facing camera on a car. The camera calibration images, test road images, and project videos are presented as output from the pipeline.

Jupyter Notebook

Deep-Learning

Implementation of Machine Learning algorithms and train models

Jupyter Notebook

Match3

Simple Match3 game coded in c++

Hadoop-Practice-Tasks

Jupyter Notebook