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Found 8 papers, 4 papers with code
A Unified Instance Segmentation Framework for Completely Occluded Objects and Dense Objects in Robot Vision Measurement
In addition, since OBBs only serve as prompts, CFNet alleviates the over-dependence on bounding box detection performance of current instance segmentation methods using OBBs for dense objects.
Linear Gaussian Bounding Box Representation and Ring-Shaped Rotated Convolution for Oriented Object Detection
We propose linear GBB (LGBB), a novel OBB representation.
Deep Clustering Survival Machines with Interpretable Expert Distributions
We learn weights of the expert distributions for individual instances according to their features discriminatively such that each instance's survival information can be characterized by a weighted combination of the learned constant expert distributions.
Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis
On the LIDC-IDRI benchmark dataset for benign-malignant classification of pulmonary nodules in CT images, our method achieves a new state-of-the-art accuracy of 95. 36\% and an AUC of 96. 54\%.
Brain Network Construction and Classification Toolbox (BrainNetClass)
The goal of this work is to introduce a toolbox namely "Brain Network Construction and Classification" (BrainNetClass) to the field to promote more advanced brain network construction methods.
Integrating Feature and Image Pyramid: A Lung Nodule Detector Learned in Curriculum Fashion
Meanwhile, our sampling strategy halves the training time of the proposal network on LUNA16.
Joint Learning for Pulmonary Nodule Segmentation, Attributes and Malignancy Prediction
Refer to the literature of lung nodule classification, many studies adopt Convolutional Neural Networks (CNN) to directly predict the malignancy of lung nodules with original thoracic Computed Tomography (CT) and nodule location.
See the Forest for the Trees: Joint Spatial and Temporal Recurrent Neural Networks for Video-Based Person Re-Identification
Accordingly, a demanding need is to recognize a person under different cameras, which is called person re-identification.
