Next, we continue our journey designing the discriminator module, which will be responsible for telling the real images from the fake ones supplied by the generator module we just designed. The concept behind the architecture is quite similar to that of the generator, with some key differences. The discriminator network receives images of a 32 x 32 x 3 dimension, which it then transforms into various representations as information propagates through deeper layers, until the dense classification layer is reached, equipped with one neuron and a sigmoid activation function. It has one neuron, since we are dealing with the binary classification task of distinguishing fake from real. The sigmoid function ensures a probabilistic output between 0 and 1, indicating how fake or real the network thinks a given image may be. Do also note the inclusion of...
Germany
Slovakia
Canada
Brazil
Singapore
Hungary
Philippines
Mexico
Thailand
Ukraine
Luxembourg
Estonia
Lithuania
Norway
Chile
United States
Great Britain
India
Spain
South Korea
Ecuador
Colombia
Taiwan
Switzerland
Indonesia
Cyprus
Denmark
Finland
Poland
Malta
Czechia
New Zealand
Austria
Turkey
France
Sweden
Italy
Egypt
Belgium
Portugal
Slovenia
Ireland
Romania
Greece
Argentina
Malaysia
South Africa
Netherlands
Bulgaria
Latvia
Australia
Japan
Russia