Kaggle: Cell Instance Segmentation

Last update: Aug 12, 2022

Overview

Kaggle: Cell Instance Segmentation

The goal of this challenge is to detect cells in microscope images.

with simple view on how many cels have been annotated per image:

Experimentation

install this tooling

A simple way how to use this basic functions:

! pip install https://github.com/Borda/kaggle_cell-inst-segm/archive/refs/heads/main.zip

run notebooks in Kaggle

local notebooks

some results

Training progress with EfficientNet3D with training for 10 epochs > over 96% validation accuracy:

Owner

Jirka Borovec

Computer Vision & Machine Learning & Bio-Medical Imaging & DeepLearn

GitHub Repository

MagFace: A Universal Representation for Face Recognition and Quality Assessment

MagFace MagFace: A Universal Representation for Face Recognition and Quality Assessment in IEEE Conference on Computer Vision and Pattern Recognition

523 Jan 05, 2023

[CVPR 2022] Pytorch implementation of "Templates for 3D Object Pose Estimation Revisited: Generalization to New objects and Robustness to Occlusions" paper

template-pose Pytorch implementation of "Templates for 3D Object Pose Estimation Revisited: Generalization to New objects and Robustness to Occlusions

92 Dec 28, 2022

Latex code for making neural networks diagrams

PlotNeuralNet Latex code for drawing neural networks for reports and presentation. Have a look into examples to see how they are made. Additionally, l

18.6k Jan 01, 2023

Detection of PCBA defect

Detection_of_PCBA_defect Detection_of_PCBA_defect Use yolov5 to train. $pip install -r requirements.txt Detect.py will detect file(jpg,mp4...) in cu

6 Nov 28, 2022

Learning to Map Large-scale Sparse Graphs on Memristive Crossbar

Release of AutoGMap:Learning to Map Large-scale Sparse Graphs on Memristive Crossbar For reproduction of our searched model, the Ubuntu OS is recommen

2 Aug 23, 2022

Official implementation of the paper DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows

DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows Official implementation of the paper DeFlow: Learning Complex Im

86 Nov 16, 2022

The code is the training example of AAAI2022 Security AI Challenger Program Phase 8: Data Centric Robot Learning on ML models.

Example code of [Tianchi AAAI2022 Security AI Challenger Program Phase 8]

22 Oct 14, 2022

A curated list of awesome Active Learning

Awesome Active Learning 🤩 A curated list of awesome Active Learning ! 🤩 Background (image source: Settles, Burr) What is Active Learning? Active lea

431 Jan 03, 2023

The Dual Memory is build from a simple CNN for the deep memory and Linear Regression fro the fast Memory

Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of

1 Jan 27, 2022

Federated Learning - Including common test models for federated learning, like CNN, Resnet18 and lstm, controlled by different parser

Federated_Learning 💻 This projest include common test models for federated lear

10 Dec 11, 2022

Kaggle: Cell Instance Segmentation

Related tags

Overview

Kaggle: Cell Instance Segmentation

Experimentation

install this tooling

run notebooks in Kaggle

local notebooks

some results

Owner

Jirka Borovec

MagFace: A Universal Representation for Face Recognition and Quality Assessment

[CVPR 2022] Pytorch implementation of "Templates for 3D Object Pose Estimation Revisited: Generalization to New objects and Robustness to Occlusions" paper

Latex code for making neural networks diagrams

Detection of PCBA defect

Learning to Map Large-scale Sparse Graphs on Memristive Crossbar

Official implementation of the paper DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows

The code is the training example of AAAI2022 Security AI Challenger Program Phase 8: Data Centric Robot Learning on ML models.

A curated list of awesome Active Learning

The Dual Memory is build from a simple CNN for the deep memory and Linear Regression fro the fast Memory

Federated Learning - Including common test models for federated learning, like CNN, Resnet18 and lstm, controlled by different parser

Code for paper: Towards Tokenized Human Dynamics Representation

Disturbing Target Values for Neural Network regularization: attacking the loss layer to prevent overfitting

A PyTorch Implementation of "Neural Arithmetic Logic Units"

Code for our paper "Graph Pre-training for AMR Parsing and Generation" in ACL2022

RIM: Reliable Influence-based Active Learning on Graphs.

Global-Local Context Network for Person Search

PixelPyramids: Exact Inference Models from Lossless Image Pyramids (ICCV 2021)

Medical-Image-Triage-and-Classification-System-Based-on-COVID-19-CT-and-X-ray-Scan-Dataset

Code for ACL2021 paper Consistency Regularization for Cross-Lingual Fine-Tuning.

An AutoML Library made with Optuna and PyTorch Lightning