The study focuses on the development of an attack-resilient Generative Adversarial Network (AR-GAN) for traffic sign classification in autonomous vehicles (AVs). AVs rely on Deep Neural Network (DNN)-based systems to…
Continue readingAVs utilize deep neural network (DNN)-based classification systems to identify traffic signs. However, these models are susceptible to adversarial attacks that can cause misclassification by introducing slight perturbations to an…
Continue readingThe article discusses AR-GAN, a Generative Adversarial Network-based defense method against adversarial attacks on the Traffic Sign Classification System of Autonomous Vehicles. The AR-GAN classification system includes a generator that…
Continue readingRA VEN is a novel unconditional video generative model designed to address long-term spatial and temporal dependencies. It uses a hybrid explicit-implicit tri-plane representation to model an entire video sequence….
Continue readingThe paper presents a new trajectory prediction model, Social Force Generative Adversarial Network (SoFGAN), for human-robot collaboration. It uses a Generative Adversarial Network (GAN) and Social Force Model (SFM) to…
Continue readingThe article presents a model for symbolic music generation that is controlled by emotions. This model combines diffusion models with Generative Adversarial Networks (GANs). While diffusion models have been successful…
Continue readingThis paper presents CrossSinger, a cross-lingual singing voice synthesizer based on Xiaoicesing2. The system is notable for its ability to produce high-fidelity singing voices from monolingual singers in multiple languages….
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