Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 8 of 8 for “"Adversarial Attack And Defense"”.
-
Person Re-identification and an Adversarial Attack and Defense for Person Re-identification Networks
… of interest. There has been great interest and significant progress in person ReID, which is important for security and wide-area surveillance applications as well as human computer interaction systems. In order to continuously track targets across multiple cameras with disjoint views, it is …
-
Person Re-identification And An Adversarial Attack And Defense For Person Re-identification Networks
… of interest. There has been great interest and significant progress in person ReID, which is important for security and wide-area surveillance applications as well as human computer interaction systems. In order to continuously track targets across multiple cameras with disjoint views, it is …
-
Peer-to-peer network modeling for adversarial proactive cyber defenses
… co-evolutionary algorithms in order to model adversarial attack and defense dynamics in networks. Modeling this behavior is desirable as it allows for network designers to better develop network defense strategies against adaptive cyber attackers. By developing a network simulator that …
-
AI-infused security: Robust defense by bridging theory and practice
… Intelligence (AI) has tremendous potential as a defense against real-world cybersecurity threats, understanding the capabilities and robustness of AI remains a fundamental challenge. This dissertation tackles problems essential to successful deployment of AI in security settings and is comprised …
-
Mathematical Optimization Algorithms for Model Compression and Adversarial Learning in Deep Neural Networks
… such as image recognition, speech recognition and self-driving cars. However, their large model size and computational requirements add a significant burden to state-of-the-art computing systems. Weight pruning is an effective approach to reduce the model size and computational requirements of …
-
Energy Efficient Deep Spiking Recurrent Neural Networks: A Reservoir Computing-Based Approach
… widely used for supervised pattern recognition and exploring the underlying spatio-temporal correlation. However, due to the vanishing/exploding gradient problem, training a fully connected RNN in many cases is very difficult or even impossible. The difficulties of training traditional RNNs, led …
-
Trustworthy machine learning throughout model’s life cycle
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms