Vassilis Tsagaris and Dimitris Kastaniotis at Irida Labs say an iterative approach is needed to build a real-world AI vision application on embedded hardware
Basler's embedded vision development kit, which won an Embedded World award, along with numerous other vision technology for embedded processing, was on display during the Embedded World trade fair at the end of February in Nuremberg, Germany
Irida Labs (3A-549) will display EVLib, a deep learning-based software library
Deep learning technology will be in abundance at the upcoming Vision show in Stuttgart from 6 to 8 November, where first-time exhibitors Sualab, Deepsense, and Neadvance will show AI solutions
Dr Christos Theoharatos, chief scientific officer at Irida Labs, describes an imaging system for monitoring the melt pool in additive manufacturing, developed as part of a Horizon 2020 project
With recent new product releases offering support for GPUs, more vision engineers are starting to design embedded systems. Greg Blackman reports on the rise of embedded vision
With the Greek economic crisis providing the backdrop, Greg Blackman reports from the European Machine Vision Association's business conference in Athens
The sensor of SWIR Vision Systems' Acuros CQD 1920 camera
Matthew Dale finds that new sensor technologies based on quantum dots are set to bring down the cost of shortwave infrared imaging
Keely Portway finds out how vision technology is playing a role in medical diagnosis
Bob McCurrach, director of standards development at AIA, updates on the progress being made in GigE Vision
Following speaking at Embedded Vision Europe, Pierre Gutierrez, lead machine learning researcher at Scortex, writes about the challenges of deploying deep learning on the factory floor
Takashi Someda, CTO at Hacarus, on the advantages of sparse modelling AI tools
Depth map from the SceneScan. Credit: Nerian Vision
Dr Konstantin Schauwecker, CEO of Nerian Vision, describes the firm’s stereo vision sensor for fast depth perception with FPGAs
MVDK evaluation board with MIPI CSI-2 sensor and CXP interface board. Credit: Euresys
Greg Blackman finds that purchasing IP cores for FPGAs is one way to reduce time-to-market for camera production
