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Smart Cameras: Development of a user-adaptable smart camera application
To enable usage of smart camera applications for users without programming skills, a system automatizing the process of training data collection, model training and model application is to be automatized and integrated into a user-adaptable smart camera system.
Keywords: Machine Learning, Deep Learning, Neural Networks, Smart Cameras, Internet of Things, IoT, Automatization, New Technologies, Innovations, Supervised Learning
can cover a wide range of sensor tasks in industrial IoT (Internet of Things) applications. One specific task is the monitoring of manual assembly work. Hereby, with the use of Neural Network based object detection algorithms, subtasks can be recognized automatically and workers can be supported with information about realized, forgotten or upcoming work steps.
In the group Design for New Technologies (DfNT) of pd|z, we are researching solutions to enable industrial applications based on smart camera technologies together with industry partners.
Analyzing accelerators and hurdles for application development as well as limiting the expertise needed to set up a new application by simplifying the process is thereby crucial.
can cover a wide range of sensor tasks in industrial IoT (Internet of Things) applications. One specific task is the monitoring of manual assembly work. Hereby, with the use of Neural Network based object detection algorithms, subtasks can be recognized automatically and workers can be supported with information about realized, forgotten or upcoming work steps. In the group Design for New Technologies (DfNT) of pd|z, we are researching solutions to enable industrial applications based on smart camera technologies together with industry partners. Analyzing accelerators and hurdles for application development as well as limiting the expertise needed to set up a new application by simplifying the process is thereby crucial.
To enable users without any programming skills to set up a smart camera system, the goal is to develop a simplified smart camera application that can collect labelled training images for the supervised learning process of new models.
Using Google AutoML’s API or comparable services, the training and application of user input dependent classification models should be automatized. This way, the user-created training data will be used to adapt an existing model or to create a new one. Controlling the system should be possible via a simple interface (options ranging from buttons to touchscreen).
The project shall be finalized by integrating the needed hard- and software in a system that can be set up and tested in either an inhouse or industrial application.
To enable users without any programming skills to set up a smart camera system, the goal is to develop a simplified smart camera application that can collect labelled training images for the supervised learning process of new models. Using Google AutoML’s API or comparable services, the training and application of user input dependent classification models should be automatized. This way, the user-created training data will be used to adapt an existing model or to create a new one. Controlling the system should be possible via a simple interface (options ranging from buttons to touchscreen). The project shall be finalized by integrating the needed hard- and software in a system that can be set up and tested in either an inhouse or industrial application.
You are highly interested in working with Neural Networks and creating real world applications Desired are interest and skills in programming (Python preferred) Experience with the training of machine learning algorithms such as YOLO will help You work independently and are eager to interact with an industrial partner You approach problems systematically and manage your projects methodically You are a team player, curious and come up with innovative ideas You are willing to integrate into a professional work environment
We focus on human-centred product development and regard the link between research and education as the key to excellence in training. We see ourselves as a partner for industry and promote the continuous transfer of knowledge through cooperation, as well as the training and further education of students and graduates to strengthen the competitiveness of mechanical engineering industry.
We focus on human-centred product development and regard the link between research and education as the key to excellence in training. We see ourselves as a partner for industry and promote the continuous transfer of knowledge through cooperation, as well as the training and further education of students and graduates to strengthen the competitiveness of mechanical engineering industry.