Play with LEGO bricks at Embedded World Expo 2022

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Deep Vision Consulting will be present at Embedded World Exhibition 2022. How to find us? Well, visit Avnet Silica or Engicam booth and you will probably find us there, but let’s spoil it a bit what we’ll show there. The video above is part of the tutorial by the name “A step-by-step tutorial from training […]

On the edge Deep Learning with the Neural Processing Unit by i.MX 8M Plus NXP

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Being an Avnet Silica partner, Deep Vision Consulting was asked to test the NPU (Neural Processing Unit) of the i.MX 8M Plus by NXP Semiconductors, before its official launch scheduled in March at embedded world Exhibition&Conference 2021. Well, our team stressed the NPU with some really challenging deep learning tasks for computer vision and the experience was really amazing! In case on-the-edge […]

Deep Vision at the Avnet Deep Learning workshop in Bologna

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At the Deep Learning workshop in Bologna, organized by Avnet, Deep Vision Consulting got the invitation to share to the passionate goup of attendees about its experience on #deepneuralnetworks and #edgecomputing, in particular on running custom/optimized DNNs on Xilinx #ultrascale+. Thanks to Mauro Ferloni, Stefano Tabanelli and all the group from Avnet for the great […]

BOOTH @ SPS IPC DRIVES ITALY, PARMA 2018

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Special thanks to our partner and supplier Advanced Technologies, that gave the opportunity to Deep Vision Consulting to have a corner at their gorgeous stand at SPS IPC Drives, italian edition, the big fair on automation held ad Parma Expo, May 22nd-24th 2018. We showed a few treats on embedded technologies: some pose estimation on […]

MULTIPLE OBJECT TRACKING WITH MHT

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In last couple of years we had the chance to work quite a lot on Multiple Object Tracking, a very hot topic in research; differently from many other tasks in computer vision, deep learning here is (still) not the definitive technology for solving the task. However the debate is quite open. Please check MOT challenge […]

FROM KERAS TO CAFFE

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Keras is a great tool to train deep learning models, but when it comes to deploy a trained model on FPGA, Caffe models are still the de-facto standard. Unfortunately, one cannot simply take a model trained with keras and import it into Caffe. The reason is twofold: first, Caffe doesn’t offer any import functions from […]