deepNOID VS BCDU-Net

Compare deepNOID vs BCDU-Net and see what are their differences.

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deepNOID BCDU-Net
1 1
4 647
- -
0.0 0.0
about 3 years ago about 1 year ago
Python Python
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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deepNOID

Posts with mentions or reviews of deepNOID. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning deepNOID yet.
Tracking mentions began in Dec 2020.

BCDU-Net

Posts with mentions or reviews of BCDU-Net. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-18.
  • [D] Extensions to U-nets
    5 projects | /r/MachineLearning | 18 Mar 2022
    I compared a U-net, BCDU-net, and a U2-net for glacier semantic segmentation which is a pretty easy task. I don't still have the exact numbers, but U2-net was the best. I've also used a U2-net to map geologic structures which is a lot harder and the U2-net did well there too.

What are some alternatives?

When comparing deepNOID and BCDU-Net you can also consider the following projects:

Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images

muzic - Muzic: Music Understanding and Generation with Artificial Intelligence

U-2-Net - The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

GlacierSemanticSegmentation - Identify glaciers in satellite images with a U^2-Net

Machine-Learning-Game-Ideas - Game ideas generation using neural networks

DeepMalwareDetector - A Deep Learning framework that analyses Windows PE files to detect malicious Softwares.

spektral - Graph Neural Networks with Keras and Tensorflow 2.

UNetPlusPlus - [IEEE TMI] Official Implementation for UNet++

RWKV-LM - RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

medicaldetectiontoolkit - The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

unet - unet for image segmentation

perin - PERIN is Permutation-Invariant Semantic Parser developed for MRP 2020