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

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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

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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: M

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Anomaly Detection on Mars  Using Deep Learning
March 28th, 2021

Anomaly detection on the surface of Mars has a few unique challenges. For example, finding publically available datasets like landing images, using deep convolutional networks and exploring the large variety of surface anomalies. Still, a team of 30+ engineers took on t

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