Technologies / Artificial Intelligence

Deep learning in computer vision

The training offers a comprehensive approach to the application of deep learning in computer vision, combining theory and practice. The program covers the design, implementation and deployment of models for a variety of image processing tasks. During the intensive workshop, participants work on real use cases, learning to solve practical problems using the latest deep learning techniques in the field of computer vision.

Issues

Digital image processing
CNN Architecture
Object detection
Semantic segmentation
Data augmentation
Transfer learning
Few-shot learning
Attention mechanisms
Edge deployment
Monitoring of models
Performance optimization
Adaptive learning

Benefits

The participant will gain a thorough theoretical and practical knowledge of implementing deep learning in computer vision tasks
Will develop the ability to independently design and train advanced CNN models for a variety of computer vision applications
Will learn to effectively prepare and augment image data for deep learning tasks
Will learn methods to optimize and tune computer vision models for performance and accuracy
Will be able to implement models on edge devices taking into account hardware limitations
Will gain a working knowledge of monitoring and adaptive learning of computer vision models

Who is this training for?

ML engineers specializing in image analysis

Programmers of applications using computer vision

Data Scientists working on computer vision projects

Researchers in image processing

Vision process automation specialists

Developers of image recognition systems

Prerequisites

Knowledge of the basics of deep learning
Experience in Python programming
Basic knowledge of image processing
Knowledge of linear algebra and statistics

Training program

Image feature extraction
Image representations in deep learning
Image data preparation
Network architectures for computer vision
CNN Advanced Architectures
Object detection networks
Semantic segmentation networks

Augmentation of image data
Transfer learning in vision

Attention mechanisms
Implementation and optimization
Optimization of vision models
Deployment on edge devices

Adaptive learning

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

For Deep learning in computer vision we recommend: Knowledge of the basics of deep learning; Experience in Python programming; Basic knowledge of image processing.

What is the format and duration of this training?

The training lasts 3 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: ML engineers specializing in image analysis; Programmers of applications using computer vision; Data Scientists working on computer vision projects.