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Found 10 papers, 1 papers with code
A robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery
Many statistical machine approaches could ultimately highlight novel features of the etiology of complex diseases by analyzing multi-omics data.
Frequency-specific segregation and integration of human cerebral cortex: an intrinsic functional atlas
The frequency-specific coupling mechanism of the functional human brain networks underpins its complex cognitive and behavioral functions.
PP-YOLO: An Effective and Efficient Implementation of Object Detector
We mainly try to combine various existing tricks that almost not increase the number of model parameters and FLOPs, to achieve the goal of improving the accuracy of detector as much as possible while ensuring that the speed is almost unchanged.
Ranked #106 on
Object Detection
on COCO test-dev
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 generalized kernel machine approach to identify higher-order composite effects in multi-view datasets
In this paper, we propose a novel generalized kernel machine approach to identify higher-order composite effects in multi-view biomedical datasets.
Solution for Large-Scale Hierarchical Object Detection Datasets with Incomplete Annotation and Data Imbalance
This report demonstrates our solution for the Open Images 2018 Challenge.
Training Auto-encoders Effectively via Eliminating Task-irrelevant Input Variables
Auto-encoders are often used as building blocks of deep network classifier to learn feature extractors, but task-irrelevant information in the input data may lead to bad extractors and result in poor generalization performance of the network.
An Adaptive Successive Cancellation List Decoder for Polar Codes with Cyclic Redundancy Check
In this letter, we propose an adaptive SC (Successive Cancellation)-List decoder for polar codes with CRC.
Information Theory Information Theory
