raun1
Hi. Would appreciate if you could throw your two cents on making a human-centric intelligent AI. Cephalopods are a whole new ball game.
Pinned Repositories
bath
Neuron Segmentation
ASC-NET
MICCAI 2021 | Adversarial based selective network for unsupervised anomaly segmentation
bath
Neuron Segmentation
CNN-Diffusion-MRIBrain-Segmentation
CNN based brain masking
ISBI-2020-LITS_Hybrid_Comp_Net
ISBI2018-Diagnostic-Classification-Of-Lung-Nodules-Using-3D-Neural-Networks
Network Architecture for the ISBI_2018 paper : DIAGNOSTIC CLASSIFICATION OF LUNG NODULES USING 3D NEURAL NETWORKS
Margaret-Simple-CNN-using-BigDL-and-Spark
Simple CNN using BigDL and Spark
MICCAI2018---Complementary_Segmentation_Network-Raw-Code
The following is a new architecture for robust segmentation. It may perform better than a U-Net :) for binary segmentation. I will update the code when I have some spare time within the next month. However you can simply read this one and will soon notice the pattern after a bit
Naive_Bayes_from_Scratch_Spark
Basic_naive_Bayes code
Simple_Image_processing_App
You can load an image, save it, add noise of different types, use noise reduction techniques, low pass filter(noise reduction), high pass filters(edge detection) and create pyramids
raun1's Repositories
raun1/ISBI2018-Diagnostic-Classification-Of-Lung-Nodules-Using-3D-Neural-Networks
Network Architecture for the ISBI_2018 paper : DIAGNOSTIC CLASSIFICATION OF LUNG NODULES USING 3D NEURAL NETWORKS
raun1/MICCAI2018---Complementary_Segmentation_Network-Raw-Code
The following is a new architecture for robust segmentation. It may perform better than a U-Net :) for binary segmentation. I will update the code when I have some spare time within the next month. However you can simply read this one and will soon notice the pattern after a bit
raun1/ASC-NET
MICCAI 2021 | Adversarial based selective network for unsupervised anomaly segmentation
raun1/ISBI-2020-LITS_Hybrid_Comp_Net
raun1/bath
Neuron Segmentation
raun1/CNN-Diffusion-MRIBrain-Segmentation
CNN based brain masking
raun1/Margaret-Simple-CNN-using-BigDL-and-Spark
Simple CNN using BigDL and Spark
raun1/Naive_Bayes_from_Scratch_Spark
Basic_naive_Bayes code
raun1/Simple_Image_processing_App
You can load an image, save it, add noise of different types, use noise reduction techniques, low pass filter(noise reduction), high pass filters(edge detection) and create pyramids