Student postupoval dle pokynů vedoucího / zadání práce. Dále si sám dohledal veškeré potřebné zdroje a další literaturu.

Práce byla dokončována velmi blízko termínu odevzdání. Text práce jsem měl k dispozici po celou dobu řešení. Finální verzi textu student konzultoval před odevzdáním.

Evaluation level: zadání splněno

The technical report has a logical structure, but the sub-chapter headings could be better balanced, both in content and scope. Although there are links between the chapters, some essential information is not very clear. The overall clarity of the issues and solutions presented would have been helped by a better indication of the context and reason for the text section in the introductions of the (sub)chapters. The author presents methods for explainability, but does not further specify what is the output of the different approaches and, above all, how they are interpreted and thus how they "explain" the model (e.g. Figures 3.1-3.3).

The presentation of the experiments could include a clearer and more understandable explanation of the problem the experiment aims to solve, including e.g. the ideal or worst-case outcome. While the text does include a discussion of the experiments and results, it is pretty difficult for the reader to understand their meaning. Furthermore, it is not clear why the author experiments with the two classification architectures ResNet18 and EfficientNetV2s, what are the conclusions from the "all-attacks" experiments, and which architecture is subsequently used for other experiments and scenarios. The results in Chapter 6.1 are not interpreted, but only presented. The significance of the experiments presented in Chapter 6.2 is not clear. Minor errors include e.g. missing reference to Figure (p. 23) or an error in Chapter 6.1.2 (should not be "one-attack" but "unseen-attack").

The above-mentioned shortcomings are a very demanding requirement in the given issue and therefore the presentation level of the technical report can be still assessed as good.

The author draws on 55 study sources, which are primarily scientific articles. This is a relevant selection of literature from which the author draws appropriately. It is clear from the technical report that the author understands the methods he has chosen and used for his solution. The question is, whether it would not be more appropriate to base the review of the topic on a relevant book (e.g. [28]) and then make a shortlist of publications. After all, it is a challenging task to comprehensively process almost 50 scientific publications into a somewhat more concise theoretical overview. Source [26] does not have a publisher, and source [12] would be more suited to a footnote.

The result is a trained model for Presentation Attack Detection and an analysis explaining the model behavior. The analysis is based on an appropriate procedure and is relevant. To better use the results of the work, conclusions should be drawn that would lead to further modifications of the model and analyze also other scenarios ("unseen-attack" and "one-attack"). The results can serve as a good start for further analyses in Presentation Attack Detection task as well as in other image classification tasks.