Pinned Repositories
Attention-Res-UNet-with-Guided-Decoder-for-Semantic-Segmentation-of-Brain-tumors
A new Deep Learning architecture for automatic segmentation of brain tumors.
Blog-Generation-with-LLAMA-2
App for Blog Generation using open souce LLama 2 model
QuickNAT-keras
Implementation of QuickNAT for brain tumor segmentation using Keras library with tensorflow as backend. The QuickNAT is a fast and accurate segmentation model. The model has been implemented along with the Unpooling and a combined loss function of dice score and weighted cross-entropy as described in the paper.
Semantic-Segmentation-using-UNet-on-BRATS-2019
This is a simple implementation of the U-Net architecture on the BRATS 2019 dataset for semantic segmentation task, for beginners trying to do Deep Learning projects.
SIMPLE
Molecular Dynamics SIMulation via Physics-based LEarning
Pure-Pursuit-path-tracking-algorithm
Implementation code for one of the popular path tracking algorithms - the Pure Pursuit Algorithm.
PythonRobotics
Python sample codes for robotics algorithms.
dhirajmaji7's Repositories
dhirajmaji7/Blog-Generation-with-LLAMA-2
App for Blog Generation using open souce LLama 2 model
dhirajmaji7/Attention-Res-UNet-with-Guided-Decoder-for-Semantic-Segmentation-of-Brain-tumors
A new Deep Learning architecture for automatic segmentation of brain tumors.
dhirajmaji7/Pure-Pursuit-path-tracking-algorithm
Implementation code for one of the popular path tracking algorithms - the Pure Pursuit Algorithm.
dhirajmaji7/PythonRobotics
Python sample codes for robotics algorithms.
dhirajmaji7/QuickNAT-keras
Implementation of QuickNAT for brain tumor segmentation using Keras library with tensorflow as backend. The QuickNAT is a fast and accurate segmentation model. The model has been implemented along with the Unpooling and a combined loss function of dice score and weighted cross-entropy as described in the paper.
dhirajmaji7/Semantic-Segmentation-using-UNet-on-BRATS-2019
This is a simple implementation of the U-Net architecture on the BRATS 2019 dataset for semantic segmentation task, for beginners trying to do Deep Learning projects.