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Showing 3926–3950 of 5629 papers

TitleStatusHype
Recognition of 26 Degrees of Freedom of Hands Using Model-based approach and Depth-Color Images—0
Recognition of convolutional neural network based on CUDA Technology—0
Reconstruction of Undersampled 3D Non-Cartesian Image-Based Navigators for Coronary MRA Using an Unrolled Deep Learning Model—0
Recovering Dense Tissue Multispectral Signal from in vivo RGB Images—0
Recurrent Binary Embedding for GPU-Enabled Exhaustive Retrieval from Billion-Scale Semantic Vectors—0
Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets—0
Recurring the Transformer for Video Action Recognition—0
Recursive Context Propagation Network for Semantic Scene Labeling—0
Re-designing cities with conditional adversarial networks—0
ReDistill: Residual Encoded Distillation for Peak Memory Reduction—0
RedSync : Reducing Synchronization Traffic for Distributed Deep Learning—0
Reduce Computational Complexity for Convolutional Layers by Skipping Zeros—0
Reducing Communication Overhead in Federated Learning for Network Anomaly Detection with Adaptive Client Selection—0
Reducing Memory Requirements for the IPU using Butterfly Factorizations—0
Reducing the Barriers to Entry for Foundation Model Training—0
FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training—0
Reinforced Multi-Teacher Selection for Knowledge Distillation—0
Relation Extraction Using Multiple Pre-Training Models in Biomedical Domain—0
Reliability Assessment of Neural Networks in GPUs: A Framework For Permanent Faults Injections—0
ReMotENet: Efficient Relevant Motion Event Detection for Large-scale Home Surveillance Videos—0
Removing Dynamic Objects for Static Scene Reconstruction using Light Fields—0
RenderMap: Exploiting the Link Between Perception and Rendering for Dense Mapping—0
RenderWorld: World Model with Self-Supervised 3D Label—0
Replacement Learning: Training Vision Tasks with Fewer Learnable Parameters—0
Representing Volumetric Videos as Dynamic MLP Maps—0
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