Melvin Vivas (@donvito)

Google AI Edge 관련 소식으로, LiteRT가 실시간 가속 이미지 분할을 지원한다고 발표되었습니다. Android용 핸즈온 튜토리얼(Codelab)이 제공되어 엣지 디바이스에서 이미지 분할을 가속하는 개발을 바로 실습해볼 수 있습니다.

https://x.com/donvito/status/2013158201567354899

#google #litert #imagesegmentation #android #edgeai

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

How to segment X-Ray lungs using U-Net and Tensorflow

You can find link for the code in the blog : https://eranfeit.net/how-to-segment-x-ray-lungs-using-u-net-and-tensorflow/

Check out our tutorial here : https://youtu.be/-AejMcdeOOM&list=UULFTiWJJhaH6BviSWKLJUM9sg

Enjoy
Eran

#Python #openCV #TensorFlow #ImageSegmentation #Unet #Resunet #Segmentation

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

Medical Melanoma Detection | TensorFlow U-Net Tutorial using Unet

Check out our tutorial here : https://youtu.be/P7DnY0Prb2U&list=UULFTiWJJhaH6BviSWKLJUM9sg

My blog : https://eranfeit.net/blog/

Enjoy
Eran

#Python #openCV #TensorFlow #Deeplearning #ImageSegmentation #Unet #Resunet

This tutorial provides a step-by-step guide on how to implement and train a U-Net model for persons segmentation using TensorFlow/Keras

Check out our tutorial here : https://youtu.be/ZiGMTFle7bw&list=UULFTiWJJhaH6BviSWKLJUM9sg

Enjoy
Eran

#ImageSegmentation #Unet #Resunet #MachineLearningProject #Segmentation

The unreasonable effectiveness of UNet for image segmentation?
I am focusing/fixating on segmentation models and the underlining principles I'd expect for computer (and human) vision.
1) I feel like UNet models shouldn't need all those skip-connections: the highest resolution one would do
2) I feel like the effectiveness comes from the decoder doing too much work, not only by receiving skip-connections but effectively adding many convolutions
3) I feel like fancier models that use transformer encoders UNet-like convolutional decoders incur in (2) and they're not particularly better/different
4) I think the encoder should do the heavy, semantic job; then a "pixel" would actually integrate information from its surroundings and a simple MLP decoder should suffice to classify/segment each pixel

The approaches in the biomedical field and in the industry of big players might be diverging, as Meta can use Segment Anything Model with heavy transformer encoder pretrained and trained on millions of images, while the avg biomed researcher may have some hundreds of samples and thus work at a scale where convolutional models are just better, and maybe where SAM can't be used.

#imagesegmentation #unet #visiontransformer #deeplearning

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