Online Computer Vision Training in Serbia

This instructor-led, live training in Serbia (online or onsite) is aimed at intermediate-level to advanced-level computer vision engineers, AI developers, and IoT professionals who wish to implement and optimize computer vision models for real-time processing on edge devices.

By the end of this training, participants will be able to:

• Understand the fundamentals of Edge AI and its applications in computer vision.
• Deploy optimized deep learning models on edge devices for real-time image and video analysis.
• Use frameworks like TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
• Optimize AI models for performance, power efficiency, and low-latency inference.

This instructor-led live training Serbia (available online or on-site) targets advanced professionals who aim to deepen their grasp of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.

By the end of this training, participants will be able to:

• Build and train convolutional neural networks (CNNs) using TensorFlow.
• Leverage Google Colab for scalable and efficient cloud-based model development.
• Implement image preprocessing techniques for computer vision tasks.
• Deploy computer vision models for real-world applications.
• Use transfer learning to enhance the performance of CNN models.
• Visualize and interpret the results of image classification models.

This instructor-led, live training in Serbia (online or onsite) is aimed at intermediate-level AI developers and computer vision engineers who wish to build robust vision systems for autonomous driving applications.

By the end of this training, participants will be able to:

• Understand the fundamental concepts of computer vision in autonomous vehicles.
• Implement algorithms for object detection, lane detection, and semantic segmentation.
• Integrate vision systems with other autonomous vehicle subsystems.
• Apply deep learning techniques for advanced perception tasks.
• Evaluate the performance of computer vision models in real-world scenarios.

This instructor-led, live training in Serbia (online or onsite) is designed for beginner-level law enforcement officers who wish to transition from manual facial sketching to utilizing AI tools for developing facial recognition systems.

By the end of this training, participants will be able to:

• Understand the core principles of Artificial Intelligence and Machine Learning.
• Learn the basics of digital image processing and its application in facial recognition.
• Develop proficiency in using AI tools and frameworks to build facial recognition models.
• Gain hands-on experience in creating, training, and testing facial recognition systems.
• Understand ethical considerations and best practices in the use of facial recognition technology.

This practical training in Serbia focuses on the fundamentals of Fiji and ImageJ for biological research. Participants will develop essential skills in image preprocessing, quantitative analysis, and macro automation, enabling them to streamline workflows for histological tissues, cells, and other samples while ensuring reproducible results.

This instructor-led, live training in Serbia (online or onsite) targets intermediate-level professionals aiming to utilize Vision Builder AI for the design, implementation, and optimization of automated inspection systems within SMT (Surface-Mount Technology) processes.

Upon completion of this training, participants will be capable of:

• Setting up and configuring automated inspections using Vision Builder AI.
• Acquiring and preprocessing high-quality images for analysis.
• Implementing logic-based decision-making for defect detection and process validation.
• Generating inspection reports and optimizing overall system performance.

This live, instructor-led training in Serbia, offered online or on-site, is designed for intermediate to advanced developers, researchers, and data scientists aiming to implement real-time object detection using YOLOv7.

By the conclusion of this program, participants will be capable of:

• Understanding the foundational concepts of object detection.
• Installing and configuring YOLOv7 for detection tasks.
• Training and testing custom object detection models using YOLOv7.
• Integrating YOLOv7 with diverse computer vision frameworks and tools.
• Diagnosing and fixing common issues in YOLOv7 implementations.