TY  - JOUR
T1  - Colorimeter Using Artificial Neural Networks
AU - Pramparo, Laura AU - Moreno, Robinson Jimenez 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 20
SP  - 5332
EP  - 5337
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.5332.5337
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.5332.5337
KW  - Convolutional neural network
KW  -fully-connected neural network
KW  -colorimeter
KW  -neural network architectures
KW  -colors
AB  - The following study presents the development of a color classification algorithm for convolutional
neural networks and fully-connected neural networks which uses a database of 200 images per color and
between 12 and 18 colors to be classified for the training of the two networks. Subsequently, a comparison was
made between their accuracy percentages where the best results were 95.33% for the convolutional neural
network and 93.33% for the fully connected in the recognition of 12 colors and 93.67 and 35.23% for 18 colors,
respectively. Finally, the best network is selected to design a video recognition application and the results are
presented.
ER  -