| List |
| Topic: | Hluboká neuronová síť pro detekci objektů za ztížených snímacích podmínek |
|---|---|
| Department: | Katedra kybernetiky |
| Supervisor: | Ing. Michal Reinštein, Ph.D. |
| Announce as: | Diplomová práce, Bakalářská práce, Semestrální projekt |
| Description: | The aim is to design and implement Deep Neural Network (DNN)[1, 2, 3] based solution for object detection in difficult environment of the DARPA SubT Challenge. Objects to be detected are specified in [4]; proprietary dataset is provided, including the labels. Understanding the dataset as well as the analysis of the state-of-the-art solutions in deep learning methods is integral part of the work. |
| Bibliography: | [1] Goodfellow, Ian, et al. „Deep Learning“, MIT Press, 2016
[2] Tan, Mingxing, and Quoc V. Le. "Efficientnet: Rethinking model scaling for convolutional neural networks." arXiv preprint arXiv:1905.11946 (2019). [3] Zhang, Aston, et al. "Dive into deep learning." Unpublished Draft. Retrieved 19 (2019): 2019. https://d2l.ai/index.html [4] DARPA SubT Challenge https://www.subtchallenge.com/resources/SubT_Cave_Artifacts_Specification.pdf |