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Deep Prototypical Networks With Hybrid Residual Attention for Hyperspectral Image Classification
A hyperspectral image is basically a picture that has been taken using a special camera that can capture different wavelengths of light (like infrared…
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Deep Learning for Multi-Modal Classification of Cloud, Shadow and Land Cover Scenes in PlanetScope and Sentinel-2 Imagery
Use examples when they help make things clearer. In recent years, there have been significant advancements in deep learning techniques for multi-modal classification of…
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Deep Learning for Land Cover Classification
That’s where deep learning comes in! Deep learning is like having a really smart friend who can help you figure out what’s happening in…
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Deep Learning for Land Cover Classification of Satellite Imagery using Python
This is a fancy way of saying we’re gonna use computers to figure out what kind of stuff is on the ground based on…
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Deep Learning for Satellite Image Classification
Essentially, we’re using a computer to look at pictures from space (satellite images) and figure out what they show us. But instead of having…
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Land Classification on Sentinel 2 Data using Deep Learning CNN
Use examples when they help make things clearer. Land classification using deep learning CNN (Convolutional Neural Networks) involves analyzing satellite imagery and identifying patterns…
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Optimizing LLaMA for Triton GPTQ Kernels
Use examples when they help make things clearer. Let me break it down for you. Imagine you have a really big model, like LLaMA…
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GPTQ for LLaMa: A Comprehensive Guide to Quantization and Model Optimization
Here’s how it works: first, we quantize the weights in the model by rounding them down to the nearest integer value. This reduces the…
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Optimizing GPTQ for FP16 and nf4-double_quant on NVIDIA GPUs
Use examples when they help make things clearer. Let me break it down for you! Imagine you have a large dataset of images, and…
