Search Constraints
Number of results to display per page
Results for:
Self-awareness
Remove constraint Self-awareness
Polyu oer sim
No
Remove constraint Polyu oer sim: No
1 - 10 of 10
Search Results
-
Video
This channel walks you through the entire process of learning to code in Python; all the way from basics to advanced machine learning and deep learning. The primary emphasis will be on image processing and other relevant functionality. Why did I create this channel? To help you (students and researchers) gain a new skill and succeed in your respective fields.
You may think coding is hard and that it's not your cup of tea, but Python made it easy to code even advanced algorithms. In addition, coding will make you self sufficient, it will teach you how to think, it improves your collaborative skills and it can take your career to new heights. Therefore, if you want to stay ahead of your peers and relevant in your field, overcome your fears and start coding!
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Video
-
MOOC
In autonomous vehicles such as self-driving cars, we find a number of interesting and challenging decision-making problems. Starting from the autonomous driving of a single vehicle, to the coordination among multiple vehicles. This course will teach you the fundamental mathematical model for many of these real-world problems. Key topics include Markov decision process, reinforcement learning and event-based methods as well as the modelling and solving of decision-making for autonomous systems. This course is aimed at learners with a bachelor's degree or engineers in the automotive industry who need to develop their knowledge in decision-making models for autonomous systems. Enhance your decision-making skills in automotive engineering by learning from Chalmers, one of the top engineering schools that distinguished through its close collaboration with industry.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Decision making Automobiles -- Design construction Automated vehicles
- Resource Type:
- MOOC
-
MOOC
In this course, we will introduce you to the fundamentals of sensor fusion for automotive systems. Key concepts involve Bayesian statistics and how to recursively estimate parameters of interest using a range of different sensors. The course is designed for students who seek to gain a solid understanding of Bayesian statistics and how to use it to fuse information from different sensors. We emphasize object positioning problems, but the studied techniques are applicable much more generally. The course contains a series of videos, quizzes and hand-on assignments where you get to implement many of the key techniques and build your own sensor fusion toolbox. The course is self-contained, but we highly recommend that you also take the course ChM015x: Multi-target Tracking for Automotive Systems. Together, these courses give you an excellent foundation to tackle advanced problems related to perceiving the traffic situation around an autonomous vehicle using observations from a variety of different sensors, such as, radar, lidar and camera.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Automobiles -- Electronic equipment Automotive sensors
- Resource Type:
- MOOC
-
MOOC
Autonomous vehicles, such as self-driving cars, rely critically on an accurate perception of their environment. In this course, we will teach you the fundamentals of multi-object tracking for automotive systems. Key components include the description and understanding of common sensors and motion models, principles underlying filters that can handle varying number of objects, and a selection of the main multi-object tracking (MOT) filters. The course builds and expands on concepts and ideas introduced in CHM013x: ""Sensor fusion and nonlinear filtering for automotive systems"". In particular, we study how to localize an unknown number of objects, which implies various interesting challenges. We focus on cameras, laser scanners and radar sensors, which are all commonly used in vehicles, and emphasize on situations where we seek to track nearby pedestrians and vehicles. Still, most of the involved methods are more general and can be used for surveillance or to track, e.g., biological cells, sports athletes or space debris. The course contains a series of videos, quizzes and hands-on assignments where you get to implement several of the most important algorithms. Learn from award-winning and passionate teachers to enhanceyour knowledge at the forefront of research on self-driving vehicles. Chalmers is among the top engineering schools that distinguish itself through its close collaboration with industry.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Automobiles -- Design construction Computer vision Automated vehicles
- Resource Type:
- MOOC
-
Video
This video explores the protective systems that keep the power grid from self destructing. We usually think of the power grid in terms of its visible parts: power plants, high-voltage lines, and substations. But, much of the complexity of power grid comes in how we protect it when things go wrong. When your power goes out, it’s easy to be frustrated at the inconvenience, but consider also being thankful that it probably means things are working as designed to protect the grid as a whole and ensure a speedy and cost-effective repair to the fault.
- Subjects:
- Building Services Engineering and Electrical Engineering
- Keywords:
- Electric power failures -- Prevention Electric power distribution Electric power failures
- Resource Type:
- Video
-
Video
This video explores the challenges of self-driving cars and possible solutions to address the safety of self-driving technology.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Automobiles -- Automatic control Automobile industry trade -- Technological innovations
- Resource Type:
- Video
-
Video
From self-healing asphalt to electrified roads, technology is steering the future of driving along some exciting new paths!
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Traffic safety Roads -- Technological innovations Automobile driving
- Resource Type:
- Video
-
Courseware
This is an interdisciplinary, project-based course, centered around a design project in which small teams of students work closely with a person with a disability in the Cambridge area to design a device, piece of equipment, app, or other solution that helps them live more independently.
- Subjects:
- Biomedical Engineering, Mechanical Engineering, Rehabilitation Sciences, Computing, and Electrical Engineering
- Keywords:
- Self-help devices for people with disabilities
- Resource Type:
- Courseware
-
e-book
Machine learning techniques have the potential of alleviating the complexity of knowledge acquisition. This book presents today’s state and development tendencies of machine learning. It is a multi-author book. Taking into account the large amount of knowledge about machine learning and practice presented in the book, it is divided into three major parts: Introduction, Machine Learning Theory and Applications. Part I focuses on the introduction to machine learning. The author also attempts to promote a new design of thinking machines and development philosophy. Considering the growing complexity and serious difficulties of information processing in machine learning, in Part II of the book, the theoretical foundations of machine learning are considered, and they mainly include self-organizing maps (SOMs), clustering, artificial neural networks, nonlinear control, fuzzy system and knowledge-based system (KBS). Part III contains selected applications of various machine learning approaches, from flight delays, network intrusion, immune system, ship design to CT and RNA target prediction. The book will be of interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is intended for both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as a reference for software professionals and practitioners.
- Course related:
- COMP4432 Machine Learning
- Subjects:
- Computing
- Keywords:
- Machine learning
- Resource Type:
- e-book
-
Courseware
Students of this course will develop a broad understanding of Lean/Six Sigma principles and practices, build capability to implement Lean/Six Sigma initiatives in manufacturing operations, and learn to operate with awareness of Lean/Six Sigma at the enterprise level. All course materials are organized around a common "single-point lesson" (SPL) format, with some of the SPLs provided by the instructor and guests and with some developed and delivered by student teams.
- Subjects:
- Management and Computing
- Keywords:
- Quality control Six sigma (Quality control stard)
- Resource Type:
- Courseware
-
