#imagesegmentation — Public Fediverse posts

Top 10 Image Annotation Services Transforming Computer Vision in 2026

Explore the leading Image Annotation Services transforming AI in 2026. These top providers offer expert labeling for object detection, segmentation, and classification, helping build robust computer vision models across industries like healthcare, autonomous driving.

Know More: https://telegra.ph/Top-10-Image-Annotation-Services-Shaping-Computer-Vision-in-2026-12-08

#imageannotation #datalabeling #imagesegmentation #objectdetection #techtrends2026

Building a simple medical image segmentation tool in #JuliaLang.

So far the method only creates raw contours. Next I need to add contour cutting, merging, spline based smoothing, growing/shrinking, manual drawing, etc. and before you know it we have a high performance and #opensource tool for medical image segmentation!

#ImageSegmentation #ImageProcessing #Biomechanics #Makie

Ref above, see also https://starbeamrainbowlabs.com/blog/article.php?article=posts/538-nldl2024-paper-out.html, which includes discussion of the paper & links to blog posts that detail my progress etc

#AI #Rainfall #Paper #Floods #Flooding #Predictions #ComputerVision #ImageSegmentation #Abuse #OfAIModels #OkayNotReally

Next #definingai post is out!

Defining AI: Image segmentation

https://starbeamrainbowlabs.com/blog/article.php?article=posts%2F544-defining-ai-image-segmentation.html

#blogpost #ai #imagesegmentation #segmentation #computervision

"Tracking Anything with Decoupled #VideoSegmentation"

Demo 🎞️: https://youtu.be/FbK3SL97zf8

✍️ Cheng, Ho Kei, et al. "Tracking Anything with Decoupled Video Segmentation." #arXiv preprint arXiv:2309.03903 (2023)
🌍 https://arxiv.org/abs/2309.03903 / https://hkchengrex.com/Tracking-Anything-with-DEVA/

#MachineLearning #ImageSegmentation

I've submitted a paper to #nldl2024! This is my first real #conference submission.

Title: Towards AI for approximating hydrodynamic simulations as a 2D segmentation task

Alternate title: Abusing image segmentation to approximate physics based simulations /lh

https://www.nldl.org/

#AI #imagesegmentation #hydrodynamic #deeplabv3plus #nldl

I've submitted a paper to #nldl2024! This is my first real #conference submission.

Title: Towards AI for approximating hydrodynamic simulations as a 2D segmentation task

Alternate title: Abusing image segmentation to approximate physics based simulations /lh

https://www.nldl.org/

#AI #imagesegmentation #hydrodynamic #deeplabv3plus #nldl

I've submitted a paper to #nldl2024! This is my first real #conference submission.

Title: Towards AI for approximating hydrodynamic simulations as a 2D segmentation task

Alternate title: Abusing image segmentation to approximate physics based simulations /lh

https://www.nldl.org/

#AI #imagesegmentation #hydrodynamic #deeplabv3plus #nldl

Newly added to the Trade-Free Directory:

Segment Anything Model (SAM)

The Segment Anything Model (SAM) produces high quality object masks from input prompts such as points or boxes, and it can be used to generate masks for all objects in an image. It has been trained on a dataset of 11 million images and 1.1 billion masks, and has strong zero-shot performance on a variety of segmentation tasks.

#image-segmentation

More here:

https://www.directory.trade-free.org/goods-services/segment-anything-model-sam/

Quick #ai #deeplearning tip about sensitivity vs specificity:

I can never remember which is which, but think of it like a camera.

* Sensitivity: If the camera's sensitivity (e.g. ISO) isn't high enough, it won't see anything (positive).
* Specificity: If the image is out of focus, it will be blurry and the bit you're interested in will overflow into the negative region.

#imagesegmentation

I have this silly question about #imagesegmentation. So is there any advantage to using different software for image segmentation? I see #ImageJ, #CellProfiler, #Napari and #Python all can do this, but if the underlying algorithm is the same, then why not just stick with ImageJ?

I have this silly question about #imagesegmentation. So is there any advantage to using different software for image segmentation? I see #ImageJ, #CellProfiler, #Napari and #Python all can do this, but if the underlying algorithm is the same, then why not just stick with ImageJ?

I have this silly question about #imagesegmentation. So is there any advantage to using different software for image segmentation? I see #ImageJ, #CellProfiler, #Napari and #Python all can do this, but if the underlying algorithm is the same, then why not just stick with ImageJ?

I have this silly question about #imagesegmentation. So is there any advantage to using different software for image segmentation? I see #ImageJ, #CellProfiler, #Napari and #Python all can do this, but if the underlying algorithm is the same, then why not just stick with ImageJ?

I have this silly question about #imagesegmentation. So is there any advantage to using different software for image segmentation? I see #ImageJ, #CellProfiler, #Napari and #Python all can do this, but if the underlying algorithm is the same, then why not just stick with ImageJ?