Computer Vision
By
Vihar Kurama
Attention Mechanisms in Computer Vision: CBAM
This post covers an in-depth analysis of the Convolution Block Attention Module (CBAM) with a short introduction to Visual Attention Mechanisms.
Fighting Coronavirus with AI, Part 2: Building a CT Scan COVID-19 Classifier Using PyTorch
Using PyTorch, we create a COVID-19 classifier that predicts whether a patient is suffering from coronavirus or not, using chest CT scans of different patients.
How to Improve YOLOv3
YOLO has been a very popular and fast object detection algorithm, but unfortunately not the best-performing. In this article I will highlight simple training heuristics and small architectural changes that can make YOLOv3 perform better than models like Faster R-CNN and Mask R-CNN.
Understanding GauGAN Part 4: Debugging Training & Deciding If GauGAN Is Right For You
In this post we cover how to tackle common training issues that may arise with GauGAN. We conclude with advice on whether GauGAN will fit your business needs or not.
Understanding GauGAN Part 3: Model Evaluation Techniques
In Part 3 of the GauGAN series we cover how to evaluate model performance, and how GauGAN compares to models like Pix2PixHD, SIMS, and CRN.
Image Captioning With AI
In this tutorial we'll break down how to develop an automated image captioning system step-by-step using TensorFlow and Keras.
Understanding GauGAN Part 2: Training on Custom Datasets
In this article we cover how to train GauGAN on your own custom dataset. This is part of a series on Nvidia GauGANs.
