Enhancing Satellite Imagery through Deep Learning

August 4th, 2021

In this article, we go through exploring different ways to enhancing satellite imagery to get the best quality images using Deep Learning. We joined one of Omdena AI Challenges in collaboration with the  World Food Program. The challenge goal is to fight hunger by loc

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Applying CNNs To Images For Computer Vision And Text For NLP

June 11th, 2021

Convolutional Neural Networks (CNNs, ConvNets) have become crucial in artificial intelligence. These networks are reputable for excellently capturing spatial and dependency information in matrices (images, sentences), while effectively reducing their sizes without disca

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Deep Learning Pipeline for Image Segmentation & Laser Weed Removal

May 20th, 2021

A Crop vs Weed Segmentation on the edge pipeline, in order to improve the model performance that identifies weed from crops in images, we used different image segmentation techniques. Here we present a walkthrough of the preprocessing and pipelining for the Semantic Se

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Optimization of Edge based Inference Pipeline for Weed Control

May 7th, 2021

This article captures, the optimizations explored for the AI-enabled edge-based weed controller on Nvidia Jetson Xavier AGX. The experiments include TensorRT quantization, calibrations, benchmarking of inference pipeline based on YolactEdge, Bonnetal models, and the enh

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Denoising Images: How to Use Autoencoders to Produce Clearer Images

April 4th, 2021

In this article, we take you into a friendly approach to denoising images and Denoising Autoencoders (DAEs), their architecture, their importance in deep learning models, how to use them with neural networks, and how they improve models’ results. Authors: Melania

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