Algolux has announced a research partnership with Mila, an academic research institution dedicated to advancing artificial intelligence, with a strong focus on deep learning related to image processing and computer vision
Reconstruction of traffic signs with high-resolution colour non-line-of-sight imaging using conventional CMOS cameras sensors
Carnegie Mellon University showed a non-line-of-sight imaging technique able to compute millimetre- and micrometre-scale shapes of curved objects
Algolux won the software innovation award at the 2018 AutoSens conference for its artificial intelligence technology for autonomous vision
Algolux, a provider of machine-learning stacks for autonomous vision, has closed a $10 million series A funding round led by General Motors Ventures. Its technology has also won best automotive solution at the Embedded Vision Summit
Canadian machine learning company, Algolux, has won the ‘Most exciting startup’ award at the AutoSens show in Brussels on 20 September
Algolux, Inc. today announced CRISP-ML, the first machine learning platform to automate the complex optimization of vision systems. The platform’s advanced technology and architecture provide a unique advantage to both experienced and novice computer vision teams in addressing the growing cost, expertise, and time to market challenges they face in optimizing their systems.
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
