AZoOptics

Deep Learning in Optical Microscopy: Advancements and Applications

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

Researchers Are Using A.I. to Decode the Human Genome

AlphaGenome is a leap forward in the ability to study the human blueprint. But the fine workings of our DNA are still largely ...
GitHub

A production-ready implementation of instance segmentation using state-of-the-art models from PyTorch and Hugging Face Transformers.

├── src/ # Source code │ ├── instance_segmentation.py # Core segmentation implementation │ └── data_generator.py # Synthetic data generation ├── web_app/ # Web interface │ └── app.py # Streamlit ...
Ecommerce Fastlane

What Are AI Algorithms? Types of AI Algorithms + Use Cases

The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...
IEEE

Certainty-Guided Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation

Abstract: Semi-supervised learning (SSL) enables the accurate segmentation of medical images with limited available labeled data. However, its performance usually lags fully supervised methods that ...
IEEE

CiSeg: Unsupervised Cross-Modality Adaptation for 3D Medical Image Segmentation via Causal Intervention

Abstract: Unsupervised domain adaptation (UDA) addresses the domain shift problem by transferring knowledge from labeled source domain data (e.g. CT) to unlabeled target domain data (e.g. MRI). While ...
GitHub

[ICLR 2026] VeloxSeg: Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation

Overview of VeloxSeg. VeloxSeg employs an encoder-decoder architecture with Paired Window Attention (PWA) and Johnson-Lindenstrauss lemma-guided convolution (JLC) on the left, using 1x1 convolution as ...