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Found 4 papers, 1 papers with code
Wildfire Smoke Detection with Cross Contrast Patch Embedding
By using two different negative instance sampling strategies on positive images and negative images respectively, the problem of supervision signal confusion caused by label diversity in the process of network training is alleviated.
Video Smoke Detection Based on Deep Saliency Network
The deep feature map is combined with the saliency map to predict the existence of smoke in an image.
Domain Adaptation from Synthesis to Reality in Single-model Detector for Video Smoke Detection
The existed researches mainly work on the adaptation to samples extracted from original annotated samples.
Deep Domain Adaptation Based Video Smoke Detection using Synthetic Smoke Images
Considering that the appearance gap (dataset bias) between synthetic and real smoke images degrades significantly the performance of the trained model on the test set composed fully of real images, we build deep architectures based on domain adaptation to confuse the distributions of features extracted from synthetic and real smoke images.
