ADOSMNet: a novel visual affordance detection network with object shape mask guided feature encoders
Visual affordance detection aims to understand the functional attributes of objects, which is
crucial for robots to achieve interactive tasks. Most existing affordance detection methods …
crucial for robots to achieve interactive tasks. Most existing affordance detection methods …
Attention and masking embedded ensemble reinforcement learning for smart energy optimization and risk evaluation under uncertainties
T Sogabe, DB Malla, CC Chen… - Journal of Renewable and …, 2022 - pubs.aip.org
Integrating residential-level photovoltaic energy generation and energy storage for the on-
grid system is essential to reduce electricity use for residential consumption from the grid …
grid system is essential to reduce electricity use for residential consumption from the grid …
Real-time adversarial GAN-based abnormal crowd behavior detection
Q Han, H Wang, L Yang, M Wu, J Kou, Q Du… - Journal of Real-Time …, 2020 - Springer
Detecting abnormal events in the crowd is a challenging problem. Insufficient samples make
those traditional model-based methods cannot cope with sophisticated anomaly monitoring …
those traditional model-based methods cannot cope with sophisticated anomaly monitoring …
Ghosm: Graph-based hybrid outline and skeleton modelling for shape recognition
B Alwaely, C Abhayaratne - ACM Transactions on Multimedia …, 2023 - dl.acm.org
An efficient and accurate shape detection model plays a major role in many research areas.
With the emergence of more complex shapes in real-life applications, shape recognition …
With the emergence of more complex shapes in real-life applications, shape recognition …