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Despite their impact on computer vision and face recognition, the inner workings of deep convolutional neural networks (CNNs) have traditionally been regarded as uninterpretable. We demonstrate this to be false by proposing prediction gradients to understand how neural networks encode concepts into individual units. In constrast, existing efforts to understand convolutional nets focus on visualizing...
Surveying a large amount of small sub-kilometer craters in planetary images is a challenging task due to their non-distinguishable features. In this paper, we integrate the LASSO (Least Absolute Shrinkage and Selection Operator) method with the Bayesian network classifier and propose an L1 Regularized Bayesian Network Classifier (L1-BNC) algorithm for this task. The L1-BNC algorithm uses the LASSO...
Information on the World Wide Web is congested with large amounts of news contents. Recommendation, filtering, and summarization of Web news have received much attention in Web intelligence, aiming to find interesting news and summarize concise content for users. In this paper, we present our research on developing the Personalized News Filtering and Summarization system (PNFS). An embedded learning...
In order to accurately extract various color regions in a color image, a multi-color extraction method based on the semantic color is put forward in this paper. By introducing semantic color and establishing semantic color model, the method can rationally solve the color extraction problem. This method makes use of fuzzy clustering algorithm which distributes pixels of an image into each color area,...
In this paper, we study a new research problem of causal discovery from streaming features. A unique characteristic of streaming features is that not all features can be available before learning begins. Feature generation and selection often have to be interleaved. Managing streaming features has been extensively studied in classification, but little attention has been paid to the problem of causal...
Craters are important geographical features caused by the impacts of meteoroids. Craters have been widely studied because they contain crucial information about the age and geologic formations of planets. This paper discusses an automated crater-detection framework using knowledge discovery and data mining (KDD) process including sampling, feature selection and creation, and supervised learning methods...
The classification of stored product insects has been an important and difficult aspect of grain reserve in the world. The existing classification methods cannot acquire excellent performance. AdaBoost, an adaptive boosting algorithm, may improve the classification accuracy of any given classifier. In this paper AdaBoost is adopted to increase the performance of artificial neural network for stored...
Generally the scene of the visual surveillance using one camera is confined within certain limits. If you want to extend the surveillance area, you need multiple cameras. It attempts to detect, recognize and track certain objects from image sequences. This paper presents a simple and effective approach segmenting and tracking a moving object from a moving platform in the air such as UAV or ballonet...
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