… techniques which … cient use of neural networks which have emerged from our work and
which have been discussed in this paper. We very much hope that others will be able to enhance …

… Our third and final case study pertains to the use of neural networks for image compression
and segmentation. The study of image compression methods has been an active area of …

… In this paper, we employed a convolution neural network and proposed several training
methods to enhance the detection of small pulmonary nodules and microcalcifications on digital …

… of ways to improve neural network based image classification … image transformations to
increase the effective size of the training set. These were based on using more of the image to …

… algorithm using neural network techniques which calculates a … the network until it “figures
out” the problemsolving technique. … method overly time consuming to obtain the necessary size …

… This study focuses on how to combine a convolution neural network with AdaBoost to
enhance the image identification performance of the learning algorithms. After the convolution …

… a deep convolutional neural network using the proposed … -of-the-art methods on the challenging
PASCAL VOC 2012 … our method by a detailed experimental study that illustrates how the …

… using the UCM data set in deep neural network techniques is its relatively small size, only 100
images … deep neural network structure, where remote sensing image chips are fed into the …

… on convolutional neural networks are employed to identify fruit pictures in this … method
based on chest X-ray images that may be used in conjunction with the RTPCR test to enhance …

… Our survey will show how class-balancing oversampling in image … using PCA color
augmentation. This Data Augmentation helped reduce overfitting when training a deep neural …