Review: DUNet — Deformable U-Net for Retinal Vessels Segmentation (Biomedical Image Segmentation)
Author(s): Sik-Ho Tsang Originally published on Towards AI. Technical Review of DUNet U+007C Towards AI U-Net+DCN, Outperforms U-Net & DCN In this story, DUNet, by Tianjin University, Linkoping University, and, is briefly reviewed. DUNet, Deformable U-Net: exploits the retinal vessels’ local features …
Review: IEF — Iterative Error Feedback (Human Pose Estimation)
Author(s): Sik-Ho Tsang Originally published on Towards AI. A Review on IEF U+007C Towards AI Outperforms Tompson NIPS’14, and Tompson CVPR’15 Getting Better and Better From Left to Right With Iterative Error Feedback (IEF) In this story, IEF (Iterative Error Feedback), by …
Make Art with Math. Become an Artist
Author(s): Mishtert T Originally published on Towards AI. Phyllotaxis Not only Analysis… R can make beautiful things too… “Mathematics is the science of patterns, and nature exploits just about every pattern that there is. ” (Ian Stewart) Phyllotaxy The arrangement of leaves …
A Gentle Introduction to Graph Embeddings
Author(s): Edward Ma Originally published on Towards AI. TransE Top highlight Photo by Edward Ma on Unsplash Instead of using traditional machine learning classification tasks, we can consider using graph neural network (GNN) to perform node classification problems. By providing an explicit …
Building a Spam Detector Using Python’s NTLK Package
Author(s): Bindhu Balu Originally published on Towards AI. NTLK — Natural Language ToolKit In this part, we will go through an end to end walkthrough of building a very simple text classifier in Python 3. Our goal is to build a predictive …
4 Graph Neural Networks you Need to Know (WLG, GCN, GAT, GIN)
Author(s): Edward Ma Originally published on Towards AI. Top highlight Photo by Edward Ma on Unsplash We went through Knowledge Graph Embeddings and Random Walk in previous graph neural network stories. Knowledge graph embeddings train entity embeddings for downstream tasks. On the …
Why Batch Normalization Matters?
Author(s): Aman Sawarn Originally published on Towards AI. Understanding why batch normalization works, along with its intuitive elegance. Batch Normalization(BN) has become the-state-of-the-art right from its inception. It enables us to opt for higher learning rates and use sigmoid activation functions even …
Problem Framing: The Most Difficult Stage of a Machine Learning Project Workflow
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Framing the right problem to tackle with data in a real-world project is not very straightforward Top highlight Photo by You X Ventures on Unsplash In this article, I will discuss why …