Computer vision

Understanding the nuances of human-like intelligence

What can we find out about human intelligence by studying how machines...

Teaching robots to map large environments

A robot trying to find staff trapped in a partially collapsed mine...

3 Questions: How AI helps us monitor and support vulnerable ecosystems

Q: In your paper, you pose the query of which AI models...

Feature Detection, Part 1: Image Derivatives, Gradients, and Sobel Operator

Computer vision is an enormous area for analyzing images and videos. While many individuals are inclined to think mostly about machine learning models once they hear computer vision, in point of fact, there are...

MobileNetV2 Paper Walkthrough: The Smarter Tiny Giant

Introduction was a breakthrough in the sphere of computer vision because it proved that deep learning models don't necessarily should be computationally expensive to realize high accuracy. Last month I posted an article where...

The SyncNet Research Paper, Clearly Explained

Introduction Ever watched a badly dubbed movie where the lips don’t match the words? Or been on a video call where someone’s mouth moves out of sync with their voice? These sync issues are greater...

The Channel-Sensible Attention | Squeeze and Excitation

After we speak about attention in computer vision, one thing that probably involves your mind first is the one utilized in the Vision Transformer (ViT) architecture. Actually, that’s not the one attention mechanism we've...

FastSAM  for Image Segmentation Tasks — Explained Simply

segmentation is a well-liked task in computer vision, with the goal of partitioning an input image into multiple regions, where each region represents a separate object. Several classic approaches from the past involved taking...

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