Unlock the Power of Deep Learning with QuantaCell’s Customized Development Services

Deep learning model design

Optimize deep learning algorithms

Integrate deep learning instruments and software solutions

Transform your data with QuantaCell’s deep learning design and build Services

At QuantaCell, we specialize in cutting-edge deep learning algorithm development.
Our team of deep learning experts has a strong understanding of the latest advancements in the AI field and can provide customized solutions for your specific needs.
We offer a comprehensive deep learning development service including:

building new deep learning models adapted to your data, constraints ,
developing and obtimizing new deep learning architectures for fast and robust processing
and deploying the solutions in industrial solution, instrument or web services.

Our programming languages of choice are Python for prototyping and C++ for industrial software, ensuring a smooth and efficient development process. Whether you need to develop a deep learning solution for a specific problem or are looking to integrate deep learning into your existing workflow, our team is here to help. With a focus on delivering high-quality results and exceptional customer service, we are confident that we can provide the deep learning development solution that your company needs. Don’t miss this opportunity to take advantage of the power of deep learning. Contact us today to learn more about our deep learning development services and how we can help you reach your goals.

Different steps in deep learning building

Preparing the data and the anotations

Maximize your model’s potential with QuantaCell’s comprehensive data preparation services, including data set curation and annotation

Prototyping the deep learning architecture

Quickly prototype and validate deep learning strategies with QuantaCell’s Python-powered architecture prototyping

Optimize your model to improve accuracy

Fine-tune your model’s accuracy with hyperparameter optimization, including learning rate selection, optimal optimizer selection, and neural network depth analysis

Embed in instruments or software solutions

Seamlessly integrate your deep learning solutions into your workflow with QuantaCell’s instrument and software embedding services

Cutting edge deep learning technologies are handled by QuantaCell

Python TensorFlow

TensorFlow is generally used in QuantaCell for academic and industrial applications

Python Keras

Keras is based on the top of TensorFlow to ease development work

Python PyTorch

We generally use PyTorch for basic research projects

OpenCV in Python and C++

OpenCV is used to load model learn in TensorFlow or Keras and executed

What else we can do ?

Perform a thorough assessment of your deep learning architecture and provide recommendations for optimization
Offer guidance on how to reduce the time spent on data annotation and concentrate manual efforts on crucial scenarios
Optimize the resources involved in your neural network to enhance the speed of both learning and prediction
Tune the hyper-parameters for optimal performance on a specific GPU card to ensure that the deep learning model leverages the hardware effectively
Provide ongoing monitoring of the deep learning task to ensure it is running optimally and identify any issues that need to be addressed

QuantaCell, Hôpital Saint Eloi, IRMB
80 av Augustin Fliche
34090 Montpellier, France

Contact
+33 (0) 9 83 33 81 90

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Unlock the Power of Deep Learning with QuantaCell’s Customized Development Services

Deep learning model design

Optimize deep learning algorithms

Integrate deep learning instruments and software solutions

Transform your data with QuantaCell’s deep learning design and build Services

Different steps in deep learning building

Preparing the data and the anotations

Maximize your model’s potential with QuantaCell’s comprehensive data preparation services, including data set curation and annotation

Prototyping the deep learning architecture

Quickly prototype and validate deep learning strategies with QuantaCell’s Python-powered architecture prototyping

Optimize your model to improve accuracy

Fine-tune your model’s accuracy with hyperparameter optimization, including learning rate selection, optimal optimizer selection, and neural network depth analysis

Embed in instruments or software solutions

Seamlessly integrate your deep learning solutions into your workflow with QuantaCell’s instrument and software embedding services

Cutting edge deep learning technologies are handled by QuantaCell

TensorFlow is generally used in QuantaCell for academic and industrial applications

Keras is based on the top of TensorFlow to ease development work

We generally use PyTorch for basic research projects

OpenCV is used to load model learn in TensorFlow or Keras and executed

What else we can do ?

Perform a thorough assessment of your deep learning architecture and provide recommendations for optimization

Offer guidance on how to reduce the time spent on data annotation and concentrate manual efforts on crucial scenarios

Optimize the resources involved in your neural network to enhance the speed of both learning and prediction

Tune the hyper-parameters for optimal performance on a specific GPU card to ensure that the deep learning model leverages the hardware effectively

Provide ongoing monitoring of the deep learning task to ensure it is running optimally and identify any issues that need to be addressed