AIcrowd | Challenges

Round 1: Completed

Round 2: Completed

Community Contribution Round: Completed

Round 4: Completed

SEAM AI

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Solution with seismiqb and custom postprocessing Validation example of custom postprocessing with short solution explanation for fourth round

HSilksong
· Over 3 years ago

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[Explainer] End-to-end solution [F1-Score (weighted) - 0.76] Solution for 4th round

MaykolCT
· Over 3 years ago

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[Explainer] W&B, Catalyst with EDA, Extra Attributes EDA, Extra Features with wandb API and Catalyst training for rapid experimentation

jyot_makadiya
· Over 3 years ago

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1st place solution Solution of the 2nd stage of Seismic facies identification challenge

ArtemVoronov
· Over 4 years ago

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[Explainer] Just a simple Video-Notebook - Starter Pack Video version of Just a Simple Notebook

santiactis
· Over 4 years ago

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[Explainer] Introduction and General Approach Final Pack! Introduction to this challenge, general approach, my approach, and what I learn from the others

leocd
· Over 4 years ago

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3rd place solution image segmentation, DeepLabV3+, efficientnet-b3, Pytorch

Mengdi
· Over 4 years ago

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[Explainer] Detectron2 & COCO Dataset 🔥 • Web Application & Visualizations • End-to-End Baseline & Tensorflow Detectron2 & COCO Dataset 🔥 • Web Application & Visualizations • End-to-End Baseline & Tensorflow

Shubhamai
· Over 4 years ago

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[Explainer] PyTorch starter 0.857 F1-Score on public LB Baseline to take part in the challenge based on pytorch+argus+albumentations+BloodAxe’s toolbelt

ivan_romanov
· Over 4 years ago

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End to End solution that gives above 80% Accuracy Updated the solution bit with some fine tuning and reshaping. The solution that able to give above 80% accuracy now.

dills
· Over 4 years ago

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[Explainer] Need extra features? Different input approach? Try Seismic Attributes! Basically it’s a math “Instagram-Snapchat-like” filter for seismic data. There are a lot of Seismic Attributes available.

leocd
· Over 4 years ago

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[Explainer] Additional Features with the Stationary Wavelet Transform (SWT) Demonstrate the use of the Stationary Wavelet Transform (SWT) to perform a frequency based decomposition (filter banks) on the input time series data

edward_beeching
· Over 4 years ago

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[Explainer] EDA in details, baseline and advanced models It covers everything that I’ve done so far to produce submissions for this contest: from data exploration to generating predictions

sergeytsimfer
· Over 4 years ago

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[Explainer]: A Noob Code-First Notebook Just some visualizations and a baseline model that we hope can help all those looking to start out.

shraddhaa_mohan
· Over 4 years ago

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[Explainer] - EDA of Seismic data by geographic axis Here’s my EDA notebook on how the seismic data varies by geographic axis, along with some ideas for training.

dipam_chakraborty
· Over 4 years ago

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[Explainer]: Seismic Facies Identification Starter Pack keras-image-segmentation package to produce a model, train it, and generate the final predictions.

santiactis
· Over 4 years ago

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