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Found 5 papers, 1 papers with code
Benchmark data and method for real-time people counting in cluttered scenes using depth sensors
A thorough evaluation on PCDS demonstrates that our technique is able to count people in cluttered scenes with high accuracy at 45 fps on a 1. 7 GHz processor, and hence it can be deployed for effective real-time people counting for intelligent transportation systems.
A Deep Learning-Based Method for Automatic Segmentation of Proximal Femur from Quantitative Computed Tomography Images
During the experiments for the entire cohort then for male and female subjects separately, 90% of the subjects were used in 10-fold cross-validation for training and internal validation, and to select the optimal parameters of the proposed models; the rest of the subjects were used to evaluate the performance of models.
A new approach to extracting coronary arteries and detecting stenosis in invasive coronary angiograms
We aim to develop an automatic algorithm by deep learning to extract coronary arteries from ICAs. In this study, a multi-input and multi-scale (MIMS) U-Net with a two-stage recurrent training strategy was proposed for the automatic vessel segmentation.
S2MS: Self-Supervised Learning Driven Multi-Spectral CT Image Enhancement
In S2MS framework, both the input and output labels are noisy images.
Knowledge Graph Driven Recommendation System Algorithm
We first use a single-layer neural network to merge individual node features in the graph, and then adjust the aggregation weights of neighboring entities by incorporating influence factors.
