TOOLS DEVELOPED FOR IMAGE RECOGNITION
The objectives of our R&D
Reduce Time-to-Market
The tools we developed allow our Data Scientists to concentrate on actual high added value tasks for algorithms conception and implementation. We create leverage on three tasks: ease image labelisation process, offer a complete documentation on image recognition libraries, automate algorithms training.
It is the ratio of time a Data Scientist spend on low added value tasks. Our tools bring it down to 20%.
2
Tools Developed
2017
Launch of our R&D
5
Dedicated Researchers
Impacts
Our tools let me focus on the code which requires the highest technical knowledge and the more human intelligence.
Chani, a dedicated tool to visually control a dataset
Build a reliable dataset
Chani, a dedicated tool to visually control a dataset
Build a reliable dataset
Accurate data is the success-driving factor for image recognition projects. Monitoring the quality of data ensures the team that the algorithm is correctly learning. What Chani offers: - 100% of the data is available for AI algorithm training - Data Scientists can create their datasets x2 faster - Data labeling is automated thanks to Deep Learning algorithms (YOLOv3, MaskRCNN)
Ibad, a library of algorithms built for image recognition
Unpuzzle image recognition algorithms
Ibad, a library of algorithms built for image recognition
Unpuzzle image recognition algorithms
Ibad allows data Scientists and project leaders to understand how algorithms train thanks to a state of the art library of image recognition algorithms. More precisely, Ibad allows to: - Refine algorithms to better solve our clients problems - Cut by three the time dedicated to defining the architecture of code - Maintain the state of the art knowledge of the image recognition ecosystem thanks to tutorials and self-learning sessions
Our R&D Team
A team of high skilled experts in Artificial Intelligence
Our R&D Team
A team of high skilled experts in Artificial Intelligence
Sicara dedicates 20% of its ressources to R&D to maintain its teams on the cutting-edge of technology in image recognition.
Antoine
Polytechnique, PhD
Tanguy
Polytechnique, PhD
Laurent
ENSTA ParisTech, PhD ENSAM
Etienne
Polytechnique
Théodore
Centrale Paris
Associated articles written by Sicara's Data Scientists
GAN with Keras: Application to Image Deblurring
A Generative Adversarial Networks tutorial applied to Image Deblurring with the Keras library.
Raphaël
Data Scientist
Keras Tutorial: Content Based Image Retrieval Using a Denoising Autoencoder
How to find similar images thanks to Convolutional Denoising Autoencoder.
Adil
Data Scientist
Set up TensorFlow with Docker + GPU in Minutes
Why Docker is the best platform to use Tensorflow with a GPU.
Reda
Data Scientist
