Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of...
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Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of green tide is presented from Landsat TM/ETM plus image which needs not the atmospheric correction. In order to achieve an automatic detection of green tide, a linear relationship(y =0.723 x+0.504) between detection threshold y and subtraction x(x=λnir–λred) is found from the comparing Landsat TM/ETM plus image with the field *** this relationship, green tide patches can be detected automatically from Landsat TM/ETM plus *** there is brightness difference between different regions in an image, the image will be divided into a plurality of windows(sub-images) with a same size firstly, and then each window will be detected using an adaptive detection threshold determined according to the discovered linear relationship. It is found that big errors will appear in some windows, such as those covered by clouds seriously. To solve this problem, the moving step k of windows is proposed to be less than the window width n. Using this mechanism, most pixels will be detected[n/k]×[n/k] times except the boundary pixels, then every pixel will be assigned the final class(green tide or sea water) according to majority rule voting strategy. It can be seen from the experiments, the proposed detection method using multi-windows and their adaptive thresholds can detect green tide from Landsat TM/ETM plus image automatically. Meanwhile, it avoids the reliance on the accurate atmospheric correction.
In this paper, we present an effective method to craft text adversarial samples, revealing one important yet underestimated fact that DNN-based text classifiers are also prone to adversarial sample attack. Specificall...
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Considering the difficulty of fruit and vegetable images with uneven illumination and uncontrolled backgrounds, this paper proposed an image preprocess algorithm based on visual subject detection. Firstly, we can use ...
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Considering the difficulty of fruit and vegetable images with uneven illumination and uncontrolled backgrounds, this paper proposed an image preprocess algorithm based on visual subject detection. Firstly, we can use manifold ranking to significance test and to acquire significance images, then use gradient images and position weighting to get cutting images, finally adjust the image brightness and remove image noise to complete the image *** experiment results demonstrated the robustness and real-time of the proposed algorithm which can segment images accurately and the accuracy is higher than 91%.
Environmental changes in the farm can have a significant impact on the healthy growth of cage pigeons, disease prevention and the quality of pigeon meat. The stability and adaptability testing of environmental monitor...
Environmental changes in the farm can have a significant impact on the healthy growth of cage pigeons, disease prevention and the quality of pigeon meat. The stability and adaptability testing of environmental monitoring equipment and systems was completed through the pilot deployment of IoT Ranch in a pigeon farm in Beijing. An integrated program for real-time monitoring of environmental parameters of cage pigeons is implemented. Moreover, a system for informatizing and researching environmental information and real-time querying information on a webpage or mobile terminal is developed. The information-integrated environmental monitoring equipment and system can provide technical support for the modernization, automation and digital management of cage pigeons.
Due to the unpredictable location, fuzzy texture and diverse shape, accurate segmentation of the kidney tumor in CT images is an important yet challenging task. To this end, we in this paper present a cascaded trainab...
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The breeding environment of laying hens has an important influence on the growth of laying hens, the prevention and control of diseases, and the yield and quality of eggs. Therefore, the real-time collection and utili...
The breeding environment of laying hens has an important influence on the growth of laying hens, the prevention and control of diseases, and the yield and quality of eggs. Therefore, the real-time collection and utilization of the environment information of laying hens is the key point of breeding laying hens. In this study, the environmental information monitoring and control equipment and systems for egg-breeding laying hens were integrated and developed. The real-time monitoring of the environment information of the laying hens and the information query function on the webpage and mobile devices was realized. The stability and versatility testing of equipment and systems were completed through the pilot deployment of equipment and systems in a laying hen farm in Beijing. The design and development of the equipment and system can provide technical support for the modernization, mechanization and information management of laying hens.
Typically, the deployment of face recognition models in the wild needs to identify low-resolution faces with extremely low computational cost. To address this problem, a feasible solution is compressing a complex face...
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The mainstream pruning robots do not have the ability to make decisions independently. The pruning schemes are all artificially generated by experts according to the collected images. In order to improve the intellige...
The mainstream pruning robots do not have the ability to make decisions independently. The pruning schemes are all artificially generated by experts according to the collected images. In order to improve the intelligence of pruning robot and reduce the labor cost of pruning work, it is necessary to study the robot pruning decision algorithm corresponding to different fruit tree varieties. In this paper, taking apples in the early fruit period as an example, referring to the technical principle of traditional fruit tree pruning and aiming at two types of interference in the pruning process, the back branches and interfering branches, a pruning decision algorithm based on BP neural network was proposed. The algorithm formed the training set by artificially collecting the accurate data of the spatial characteristics of the fruit tree branches and performed calibration for pruning type, and the neural network model was trained according to the calibrated data set. The model trained in the first stage showed the situation that the competition branches cannot be identified. Based on this, an improved algorithm was proposed to improve the classification performance of the competition branches. The experimental results verified that the F1 score of the method for the back branches was 0913; the F1 score for the centripetal branches was 0.867; the improved algorithm has an F1score of 0.755 for the competition branches; the overall conformed to the expectation, which could provide algorithm support for the pruning robot to make artificial intelligence decision.
A branch 3D Skeleton extraction method based on SR4000 is proposed, which can be used for pruning robot visual recognition. In this method a 3D Skeleton model of the branches of apple trees in the initial fruit stage ...
A branch 3D Skeleton extraction method based on SR4000 is proposed, which can be used for pruning robot visual recognition. In this method a 3D Skeleton model of the branches of apple trees in the initial fruit stage was successfully constructed. According to the experimental results, the average computational efficiency of the 2AHC(2-level Aggregation Hierarchy Clustering) is increased by 369%, the detection rate is 84.69%, and the error rate is 5.03%. The average detection rate of depth analytic hierarchy process was 64%; The overall 3D Skeleton restoration effect is better. Therefore, the algorithm can better reflect the qualitative relationship between branches, improve the computational efficiency, and provide algorithm support for automatic pruning robot visual recognition.
In this paper, we consider the problem of vehicular positioning enhancement with emerging connected vehicles (CV) technologies. In order to actually describe the scenario, the Interacting Multiple Model (IMM) filter i...
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