The Relearning system of this program will lead you to make agile progress in the implementation of a Mas RCNN to detect objects in images"

In the field of Deep Learning, Evaluation Metrics are fundamental tools for measuring and quantifying the performance of Machine Learning models. In this way, professionals use them in order to evaluate both the efficiency and quality of the models in the task for which they are specialized.  In turn, these systems enable companies to monitor progress, identify trends and make continuous adjustments aimed at improving the performance of their procedures. As a result, companies see opportunities to improve their business and differentiate themselves in the marketplace.

Given its rising relevance, TECH implements a pioneering postgraduate certificate in Segmentation with Deep Learning in Computer Vision. Its purpose is for professionals to acquire new skills and tools to carry out innovative projects. Therefore, the curriculum will provide various measurement methods such as  Dice Coefficient and Pixel Accuracy Likewise, the syllabus will delve into Cost Functions so that graduates can learn the models effectively. Similarly, the program will delve into Point Cloud Segmentation for students to gain an accurate understanding of three-dimensional environments and facilitate informed decision making.

Since this university program is developed through a 100% online methodology, the specialists will have the opportunity to combine their update with the rest of their personal and professional obligations. This is an ideal opportunity for professionals to study a quality program, with the flexibility to plan their schedules and evaluation chronograms. The only thing students will need is an electronic device with Internet access to visualize the didactic content hosted on the virtual platform.

Mastering Segmentation with Deep Learning will open up numerous career opportunities in business sectors such as healthcare, technology and automotive"

This postgraduate certificate in Segmentation with Deep Learning in Computer Vision contains the most complete and up-to-date program on the market. The most important features include:

• The development of case studies presented by experts in computer science and computer vision
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where the self-assessment process can be carried out to improve learning
• Its special emphasis on innovative methodologies 
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

You will effectively handle the STFCN architecture and leverage both spatial and temporal information to achieve robust results"

The program’s teaching staff includes professionals from the industry who contribute their work experience to this program, as well as renowned specialists from leading societies and prestigious universities. 

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations. 

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year For this purpose, the students will be assisted by an innovative interactive video system created by renowned and experienced experts.  

You will get a solid foundation to participate in the most important research projects and develop innovative algorithms"

You will enjoy dynamic learning thanks to TECH's didactic tools, including explanatory videos and case studies"

This university program in Segmentation with Deep Learning in Computer Vision will equip specialists with the latest tools in this branch of Machine Learning. In this way, they will be able to implement them in their work with immediacy to optimize their various tasks. In addition, professionals will be able to design and implement projects that include, among others, applications in object detection or computer vision. 

Adopt the latest state-of-the-art Evaluation Metrics in your daily practice in only 150 hours"

General Objectives

• Analyze semantic segmentation neural networks and their metrics
• Identify the most common architectures
• Establish Use Cases
• Apply correct cost function for learning

Specific Objectives

• Analyze how semantic segmentation networks work
• Examine evaluation metrics and different architectures
• Delve into video domains and cloud points
• Apply theoretical concepts through various examples

A comprehensive update on Image Segmentation with Deep Learning through a program designed by real specialists"