Národní úložiště šedé literatury Nalezeno 12 záznamů.  předchozí11 - 12  přejít na záznam: Hledání trvalo 0.01 vteřin. 
Laptop Touchpad Palm Detection with AI/ML
Menzyński, Mark Alexander ; Kavetskyi, Andrii (oponent) ; Drahanský, Martin (vedoucí práce)
The situation about palm rejection for laptops is less than ideal. Most research focuses on touchscreens, and there is minimal research on touchpads. Some research is possibly done privately in laptop manufacturer companies, but the technology is lacking behind regardless. This thesis explores several shallow and deep machine learning models and finds their accuracy to be very much sufficient. In addition, a real-time proof of concept is implemented to demonstrate the model's capabilities.
Retinal Blood Vessel Segmentation
Nemčeková, Barbora ; Drahanský, Martin (oponent) ; Kavetskyi, Andrii (vedoucí práce)
The retina is an important part of the human eye. Incident light is processed here and moreover, it plays an essential role in diagnosing various diseases. Its early diagnostics can prevent serious consequences, such as blindness. The most common retinal diseases include diabetic retinopathy, as a consequence of diabetes, and age-related macular degeneration. Automatic retinal vessels segmentation facilitates and speeds up the work of an ophthalmologist. This work focuses on retinal blood vessels segmentation and its further classification into thin and thick vessels. The proposed algorithm is based on morphological operations, k-means clustering, and Frangi's algorithm. Evaluation of the proposed method was performed on two publicly available datasets - Drive and HRF. The results obtained represent 69,89 % for sensitivity, 91,55 % for specificity, and 88,63 % for accuracy. Division of the vessels shows, that on average 21,50 % vessels pixels belong to thick vessels and the rest 78,50 % belong to thin vessels.

Národní úložiště šedé literatury : Nalezeno 12 záznamů.   předchozí11 - 12  přejít na záznam:
Chcete být upozorněni, pokud se objeví nové záznamy odpovídající tomuto dotazu?
Přihlásit se k odběru RSS.