TY - JOUR AU - Facultad de Ciencias Biologicas y Ambientales AU - Pedraza Dorado, Aníbal AU - Bueno García, María Gloria AU - Déniz Suárez, Óscar AU - Ruiz-Santaquiteria Alegre, Jesús AU - Sánchez Bueno, Carlos AU - Blanco Lanza, Saúl AU - Borrego Ramos, María AU - Olenici, Adriana AU - Cristóbal Pérez, Gabriel AU - Ecologia DA - 2018/05/05 PY - 2019 UR - http://hdl.handle.net/10612/9312 AB - Diatom detection has been a challenging task for computer scientist and biologist during past years. In this work, the new state of art techniques based on the deep learning framework have been tested, in order to check whether they are suitable for... LA - eng PB - SPIE KW - Ecología. Medio ambiente KW - Deep learning KW - CNN KW - RCNN KW - YOLO KW - Diatoms detection KW - Water quality TI - Lights and pitfalls of convolutional neural networks for diatom identification ER -