use latexmk

src/materialandmethods.tex

@@ -20,8 +20,7 @@ Each category comprises a set of defect-free training images and a test set of i
 
 \subsection{Methods}\label{subsec:methods}
 
-\subsubsection{Dagster}
-\subsubsection{Label-Studio}
+\subsubsection{Few-Shot Learning}
 
 \subsubsection{Jupyter Notebook}\label{subsubsec:jupyternb}
 
@@ -64,6 +63,11 @@ There are several different ResNet architectures, the most common are ResNet-18,
 
 Since the dataset is relatively small and the two class classification task is relatively easy (for such a large model) the ResNet-18 architecture is used in this practical work.
 
+\subsubsection{CAML}
+Todo
+\subsubsection{P$>$M$>$F}
+Todo
+
 \subsubsection{Softmax}
 
 The Softmax function~\eqref{eq:softmax}\cite{liang2017soft} converts $n$ numbers of a vector into a probability distribution.