A genetic algorithm based optimized convolutional neural network for face recognition - Karlupia, Namrata; Mahajan, Palak; Abrol, Pawanesh; Lehana, Parveen K. (Zielona Góra: Uniwersytet Zielonogórski)
Face recognition (FR) is one of the most active research areas in the field of computer vision. Convolutional neural networks (CNNs) have been extensively used in this field due to their good efficiency. Thus, it is important to find the best CNN parameters for its best performance. Hyperparameter optimization is one of the various techniques for increasing the performance of CNN models. Since manual tuning of hyperparameters is a tedious and time-consuming task, population based metaheuristic techniques can be used for the automatic hyperparameter optimization of CNNs. Automatic tuning of parameters reduces manual efforts and improves the efficiency of the CNN model.
Keywords: convolutional neural network (CNN); hyperparameters; genetic algorithms; deep learning; evolutionary techniques