Collision avoidance using neural networks learned by genetic algorithms

[16] Haigang Zhu, Xiaogang Chen, Weiqun Dai, Kun Fu, Qixiang Ye, and Jianbin Jiao, “Orientation robust object detection in aerial images using deep convolutional neural network,”

“A Neural Network For Composer Classification”, 19th International Society for Music Information Retrieval Conference, Paris, France, 2018.. Western classical composers:

Are Deep Neural Networks good for blind image watermarking?.. Vedran Vukotić, Vivien Chappelier,

We make the assumption that even with broad and imprecise learning, the resulting neural network (represented by the weights of its synapses) constitute a good representation of

Cyclically running all the learning tracks, the neural network learns quite well how to control the steering actuator of the vehicle, with respect to the different possible

To classify the data of the two other samples, using an equal number of classes of training and control samples, as well as using groups of semantically similar classes

Evaluating on CLEF’s Test Data Set Applying our basic model – using our simpler architecture variation, a word2vec embedding layer generating 300-dimensional vec- tors and

It is focused on comparing a neural network model trained with genetic algorithm (GANN) to a backpropagation neural network model, both used to forecast the GDP of