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Scene Recognition

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Showing 151–175 of 207 papers

TitleStatusHype
A Novel Locally Linear KNN Model for Visual Recognition—0
A Robust Indoor Scene Recognition Method based on Sparse Representation—0
ASK: Adaptively Selecting Key Local Features for RGB-D Scene Recognition—0
A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation—0
A Survey of Vision Transformers in Autonomous Driving: Current Trends and Future Directions—0
Attentional Graph Convolutional Network for Structure-aware Audio-Visual Scene Classification—0
Audio Event and Scene Recognition: A Unified Approach using Strongly and Weakly Labeled Data—0
Bags of Spacetime Energies for Dynamic Scene Recognition—0
Better Exploiting OS-CNNs for Better Event Recognition in Images—0
Capturing spatial interdependence in image features: the counting grid, an epitomic representation for bags of features—0
CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads—0
Advancing Ubiquitous Wireless Connectivity through Channel Twinning—0
CNN-LTE: a Class of 1-X Pooling Convolutional Neural Networks on Label Tree Embeddings for Audio Scene Recognition—0
Coarse-to-fine Task-driven Inpainting for Geoscience Images—0
Combining Multiple Cues for Visual Madlibs Question Answering—0
ConceptLearner: Discovering Visual Concepts from Weakly Labeled Image Collections—0
Context-Aware Multi-Task Learning for Traffic Scene Recognition in Autonomous Vehicles—0
Contrastive Visual Data Augmentation—0
ConvNets vs. Transformers: Whose Visual Representations are More Transferable?—0
Cross Domain Model Compression by Structurally Weight Sharing—0
Data-oriented Scene Recognition—0
Deep convolutional filter banks for texture recognition and segmentation—0
Deep learning for scene recognition from visual data: a survey—0
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers—0
Developing efficient transfer learning strategies for robust scene recognition in mobile robotics using pre-trained convolutional neural networks—0
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