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Found 7 papers, 3 papers with code
Self-training via Metric Learning for Source-Free Domain Adaptation of Semantic Segmentation
Instead of employing thresholding on predictions, we introduce a method to weight the gradients calculated from pseudo-labels based on the reliability of the teacher's predictions.
Analysis of Visual Reasoning on One-Stage Object Detection
Current state-of-the-art one-stage object detectors are limited by treating each image region separately without considering possible relations of the objects.
Effect of Input Size on the Classification of Lung Nodules Using Convolutional Neural Networks
In this study, we proposed a framework that analyzes CT lung screenings using convolutional neural networks (CNNs) to reduce false positives.
Self-training Guided Adversarial Domain Adaptation For Thermal Imagery
To this end, we propose a self-training guided adversarial domain adaptation method to promote generalization capabilities of adversarial domain adaptation methods.
GAIT: Gradient Adjusted Unsupervised Image-to-Image Translation
In this work, we propose an unsupervised IIT method that preserves the uniform regions after the translation.
Attentive Deep Regression Networks for Real-Time Visual Face Tracking in Video Surveillance
Visual face tracking is one of the most important tasks in video surveillance systems.
False Positive Reduction in Lung Computed Tomography Images using Convolutional Neural Networks
3D CNNs are preferred over 2D CNNs because data are in 3D, and 2D convolutional operations may result in information loss.
