Kazim Ali^*, Adnan N. Quershi

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 271-284, 2022, DOI:10.32604/iasc.2022.021296

Abstract The current development of artificial intelligence is largely based on deep Neural Networks (DNNs). Especially in the computer vision field, DNNs now occur in everything from autonomous vehicles to safety control systems. Convolutional Neural Network (CNN) is based on DNNs mostly used in different computer vision applications, especially for image classification and object detection. The CNN model takes the photos as input and, after training, assigns it a suitable class after setting traceable parameters like weights and biases. CNN is derived from Human Brain's Part Visual Cortex and sometimes performs even better than Haman visual system. However, recent research shows… More >

Kai Chen^1,*, Haoqi Zhu², Leiming Yan¹, Jinwei Wang¹

Journal on Big Data, Vol.2, No.2, pp. 71-84, 2020, DOI:10.32604/jbd.2020.012294

Abstract Adversarial examples are hot topics in the field of security in deep learning. The feature, generation methods, attack and defense methods of the adversarial examples are focuses of the current research on adversarial examples. This article explains the key technologies and theories of adversarial examples from the concept of adversarial examples, the occurrences of the adversarial examples, the attacking methods of adversarial examples. This article lists the possible reasons for the adversarial examples. This article also analyzes several typical generation methods of adversarial examples in detail: Limited-memory BFGS (L-BFGS), Fast Gradient Sign Method (FGSM), Basic Iterative Method (BIM), Iterative Least-likely… More >