![Zdjęcie profilowe: mgr inż. Jan Glinko](/assets/jan-glinko,1034950-1/photo.png)
mgr inż. Jan Glinko
Zatrudnienie
- Asystent w Katedra Systemów Decyzyjnych i Robotyki
Kontakt dla biznesu
- Lokalizacja
- Al. Zwycięstwa 27, 80-219 Gdańsk
- Telefon
- +48 58 348 62 62
- biznes@pg.edu.pl
Media społecznościowe
Kontakt
- janglink@pg.edu.pl
Asystent
- Miejsce pracy
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Budynek A Elektroniki
pokój EA 128 otwiera się w nowej karcie
Wybrane publikacje
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Training of Deep Learning Models Using Synthetic Datasets
In order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
Grasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
Grasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
wyświetlono 640 razy