The color, shape, and other appearance characteristics of the flame emitted by different flame engines are different. In order to make a preliminary judgment on the category of the device to which it belongs through s...The color, shape, and other appearance characteristics of the flame emitted by different flame engines are different. In order to make a preliminary judgment on the category of the device to which it belongs through studying exterior characteristics of the flame, this paper uses the flame of matches, lighters, and candles to simulate different types of flames. It is hoped that the flames can be located and classified by detecting the characteristics of flames using the object detection algorithm. First, different types of fire are collected for the dataset of experiments. The mmDetection toolbox is then used to build several different object detection frameworks, in which the dataset can be trained and tested. The object detection model suitable for this kind of problem is obtained through the evaluation index analysis. The model is ResNet50-based faster-region-convolutional neural network(Faster R-CNN), whose mean average-precision(mAP) is 93.6%. Besides, after clipping the detected flames through object detection, a similarity fusion algorithm is used to aggregate and classify the three types of flames. Finally, the color components are analyzed to obtain the red, green, blue(RGB) color histograms of the three flames.展开更多
The synthetic lethality(SL)relationship arises when a combination of deficiencies in two genes leads to cell death,whereas a deficiency in either one of the two genes does not.The survival of the mutant tumor cells de...The synthetic lethality(SL)relationship arises when a combination of deficiencies in two genes leads to cell death,whereas a deficiency in either one of the two genes does not.The survival of the mutant tumor cells depends on the SL partners of the mutant gene,thereby the cancer cells could be selectively killed by inhibiting the SL partners of the oncogenic genes but normal cells could not.Therefore,there is an urgent need to develop more efficient computational methods of SL pairs identification for cancer targeted therapy.In this paper,we propose a new approach based on similarity fusion to predict SL pairs.Multiple types of gene similarity measures are integrated and/c-nearest neighbors algorithm(k-NN)is applied to achieve the similarity-based classification task between gene pairs.As a similarity-based method,our method demonstrated excellent performance in multiple experiments.Besides the effectiveness of our method,the ease of use and expansibility can also make our method more widely used in practice.展开更多
基金supported by the National Natural Science Foundation of China (61871058)。
文摘The color, shape, and other appearance characteristics of the flame emitted by different flame engines are different. In order to make a preliminary judgment on the category of the device to which it belongs through studying exterior characteristics of the flame, this paper uses the flame of matches, lighters, and candles to simulate different types of flames. It is hoped that the flames can be located and classified by detecting the characteristics of flames using the object detection algorithm. First, different types of fire are collected for the dataset of experiments. The mmDetection toolbox is then used to build several different object detection frameworks, in which the dataset can be trained and tested. The object detection model suitable for this kind of problem is obtained through the evaluation index analysis. The model is ResNet50-based faster-region-convolutional neural network(Faster R-CNN), whose mean average-precision(mAP) is 93.6%. Besides, after clipping the detected flames through object detection, a similarity fusion algorithm is used to aggregate and classify the three types of flames. Finally, the color components are analyzed to obtain the red, green, blue(RGB) color histograms of the three flames.
文摘The synthetic lethality(SL)relationship arises when a combination of deficiencies in two genes leads to cell death,whereas a deficiency in either one of the two genes does not.The survival of the mutant tumor cells depends on the SL partners of the mutant gene,thereby the cancer cells could be selectively killed by inhibiting the SL partners of the oncogenic genes but normal cells could not.Therefore,there is an urgent need to develop more efficient computational methods of SL pairs identification for cancer targeted therapy.In this paper,we propose a new approach based on similarity fusion to predict SL pairs.Multiple types of gene similarity measures are integrated and/c-nearest neighbors algorithm(k-NN)is applied to achieve the similarity-based classification task between gene pairs.As a similarity-based method,our method demonstrated excellent performance in multiple experiments.Besides the effectiveness of our method,the ease of use and expansibility can also make our method more widely used in practice.
