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Deep Learning and Computer Vision in Health (6 op)

Toteutuksen tunnus: SY00CB00-3002

Toteutuksen perustiedot


Ajoitus
01.08.2026 - 31.12.2026
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Opintopistemäärä
6 op
Lähiosuus
0 op
Virtuaaliosuus
6 op
Toteutustapa
Etäopetus
Yksikkö
30 Ylemmät ammattikorkeakoulututkinnot
Toimipiste
Laurea Verkkokampus
Opetuskielet
englanti
Paikat
20 - 30
Koulutus
Degree Programme in Managing Digital Transformation in the Health Sector (NYD1), Laurea Virtual Campus
Degree Programme in Managing Digital Transformation in the Health Sector (SYD1), Laurea Virtual Campus
Opettajat
Mitha Jose
Vastuuopettaja
Mitha Jose
Opintojakso
SY00CB00

Tavoitteet

The student is able to
- Identify an image's representation across various color spaces within the frequency domain and execute common image processing operations.
- Extract and analyze fundamental features from an image, design a convolutional neural network (CNN) architecture, and create an automated learning system employing traditional algorithms for image content classification.
- Develop comprehension of the standard architecture of a convolutional neural network (CNN) and its operational principles.
- Solve a moderately intricate image classification problem involving deep learning algorithms for the identification of image objects. Utilize transfer learning or fine-tuning techniques based on pre-trained CNNs.
- Apply deep learning algorithms to identify image objects and autonomously generate multimedia content in healthcare applications. Implement these algorithms using the open CV library and TensorFlow.

Arviointiasteikko

H-5

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