The timely identification and early prevention of crop diseases are essential for improving
production. In this paper, deep convolutional-neural-network (CNN) models are …

After the Cold War, the defense industries found themselves at a crossroads. However, it
seems that they are gaining new momentum, as new technologies such as robotics and …

Accurate liver vessel segmentation is of crucial importance for the clinical diagnosis and
treatment of many hepatic diseases. Recent state-of-the-art methods for liver vessel …

The fault diagnosis of safety critical systems such as wind turbine installations includes
extremely challenging aspects that motivate the research issues considered in this paper …

This paper presents research focusing on visualization and pattern recognition based on
computer science. Although deep neural networks demonstrate satisfactory performance …

By adding carefully crafted perturbations to input images, adversarial examples (AEs) can
be generated to mislead neural-network-based image classifiers. L2 adversarial …

Deep neural networks provide good performance in the fields of image recognition, speech
recognition, and text recognition. For example, recurrent neural networks are used by image …

Making adversarial samples to fool deep neural network (DNN) is an emerging research
direction of privacy protection, since the output of the attacker's DNN can be easily changed …

With the rapid development of network technology, more and more images containing
personal identity characteristics are being released by users on open network platforms …

Deep neural networks (DNNs) provide the excellent service on deep learning tasks such as
image recognition, speech recognition, and pattern recognition. In the field of face …