The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …

In the past few years, significant progress has been made on deep neural networks (DNNs)
in achieving human-level performance on several long-standing tasks. With the broader …

Backdoor attack intends to embed hidden backdoors into deep neural networks (DNNs), so
that the attacked models perform well on benign samples, whereas their predictions will be …

Current adversarial attack research reveals the vulnerability of learning-based classifiers
against carefully crafted perturbations. However, most existing attack methods have inherent …

Deep neural networks (DNNs) have been proven vulnerable to backdoor attacks, where
hidden features (patterns) trained to a normal model, which is only activated by some …

In recent years, with rapid technological advancement in both computing hardware and
algorithm, Artificial Intelligence (AI) has demonstrated significant advantage over human …

Neural networks are vulnerable to adversarial examples, malicious inputs crafted to fool
trained models. Adversarial examples often exhibit black-box transfer, meaning that …

Unsupervised Domain adaptation methods solve the adaptation problem for an unlabeled
target set, assuming that the source dataset is available with all labels. However, the …

Face recognition has achieved great success in the last five years due to the development of
deep learning methods. However, deep convolutional neural networks (DCNNs) have been …

Backdoor attack intends to inject hidden backdoor into the deep neural networks (DNNs),
such that the prediction of the infected model will be maliciously changed if the hidden …