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.

Leto
Leto

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

30%
Extra time for a Data Scientist
100%
Data used for training purposes
Background
Background
Quotes

Our tools let me focus on the code which requires the highest technical knowledge and the more human intelligence.

Felix_Miniature

Félix Vogeli, Data Scientist @Sicara

Chani, a dedicated tool to visually control a dataset

Build a reliable dataset

Inside a computer labeling

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

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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

keras, logo, manomano, sicara

Our R&D Team

A team of high skilled experts in Artificial Intelligence

IA_Brain

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

blurry street

GAN with Keras: Application to Image Deblurring

A Generative Adversarial Networks tutorial applied to Image Deblurring with the Keras library.

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Keras Tutorial: Content Based Image Retrieval Using a Denoising Autoencoder

How to find similar images thanks to Convolutional Denoising Autoencoder.

TensorFlow, AI, Docker, GPU

Set up TensorFlow with Docker + GPU in Minutes

Why Docker is the best platform to use Tensorflow with a GPU.