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A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images
First, let me explain what semantic segmentation is it’s a process where we take an image and assign each pixel to a specific category…
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Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images
Well in this case, the authors are combining two different techniques transformers and convolutions. Transformers have been popular recently for tasks like language processing…
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Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification
Now the technical stuff: 3D-2D CNN stands for “three-dimensional convolutional neural network” which is a fancy way of saying we’re using a type of…
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Satellite Image Segmentation using Deep Learning Techniques
Use examples when they help make things clearer. Let me refine the original answer for you based on your new context: Satellite image segmentation…
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Semantic Segmentation of Satellite Imagery using U-Net & fast.ai
First off, semantic segmentation is like coloring a picture with labels instead of colors. Instead of assigning each pixel a specific hue or shade,…
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Satellite Image Segmentation using U-Net and Deep Covariance Alignment
Essentially, what we have here is a method for dividing up satellite images into smaller segments or categories. The first part of the title,…
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Automatic Detection of Solar Panels Using Unet and PyTorch for Remote Sensing
This is all done through the power of PyTorch, which is a popular open-source library used for building and training neural networks. So how…
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Solar Panel Detection using Deep Learning
We want to teach a computer how to identify those solar panels and mark them on the picture so we can see where they…
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Deep Learning for Solar Panel Recognition
Basically, what we have here is a computer program that can look at pictures of solar panels and tell you whether they are good…
