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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Object Detection for Equirectangular Projections
April 23rd, 2021

Applying commonly available Machine Learning-driven object detection frameworks to equirectangular projections images.   Author: Parit Mehta   What is a Panorama? Imagine boarding a ferry to a picturesque island with a beautiful view of the ocean from the top of a

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Learning OpenCV from Scratch to Build a Pedestrian Detector
April 10th, 2021

Introduction to OpenCV, its applications, basics of image processing, Pedestrian Detector, and YOLO detector   By Rutuja Kawade   In my childhood days, I used to often think about how the photo editing apps came to know where exactly the hair or the lips are p

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Through The Looking Glass: A Deep-Dive Into an Omdena Challenge
April 2nd, 2021

Wondering what it’s like to work on an Omdena challenge? Are you unsure of how you will be able to contribute? Don’t worry! Just walk through the looking glass (this article 😄) to enter the amazing world of collaboration and learning.   By Sneha Bahl  

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Detecting Weeds Through YolactEdge Instance Segmentation to Support Smart Farming
March 24th, 2021

By Thomas Joseph, Marjan Ghobadian Introduction In order to reach the precise classification and location of crop and weeds for smart farming, several methods such as instance and semantic segmentation are applied. The target is to reach not only high accuracy regarding

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