Implementing rotation equivariance: Group-equivariant CNN from scratch
We code up a simple group-equivariant convolutional neural network (GCNN) that is equivariant to rotation. The world may be upside down, but the network will know.
Related Articles
Open Source Databases
We had a very fun and engaging chat with Matt Yonkovit who is the Chief Experience Officer at Percona, a service provider for open source databases like MySQL, PostgreSQL, MariaDB, and RocksDB. Matt has worked as a database architect for 10 years before transitioning into consulting roles at both MySQL and Sun Microsystems. In total, he’s been working with databases and open source for nearly 25 years.
Open Source Readiness
James has a lot of experience from both the developer side and the community side of open source. We dive deep into open source communities and enterprise involvement within those communities. Some of the topics we cover include: What is an open source readiness program and why should enterprises have one in place? Open source program offices and and the benefits of contributing to open source communities
CycleGAN: Unpaired Image-to-Image Translation (Part 3)
Table of Contents CycleGAN: Unpaired Image-to-Image Translation (Part 3) Configuring Your Development Environment Need Help Configuring Your Development Environment? Project Structure Implementing CycleGAN Training Implementing Training Callback Implementing Data Pipeline and Model Training Perform Image-to-Image Translation Summary Citation Information CycleGAN:…
The post CycleGAN: Unpaired Image-to-Image Translation (Part 3) appeared first on PyImageSearch.
Setting Up And Managing Open Source Program Office’s For Enterprises
In this episode, we have an insightful and entertaining conversation with Gil Yehuda, the Senior Director of Open Source at Verizon Media. Gil is the number one expert in the world when it comes to setting up and managing Open Source Program Office’s (OSPO’s) for enterprises.
DETR Breakdown Part 3: Architecture and Details
Table of Contents DETR Breakdown Part 3: Architecture and Details DETR Architecture 🏗️ CNN Backbone 🦴 Transformer Preprocessing ⚙️ Transformer Encoder 🔄 Transformer Decoder 🔄 Prediction Heads: Feed-Forward Network ➡️🧠 Importance of DETR 🌟 🔁 End-to-End Trainability ⏩ Parallel Decoding…
The post DETR Breakdown Part 3: Architecture and Details appeared first on PyImageSearch.
