We argue that racist value judgments express beliefs that are objectively false. In our view, racist value judgments have cognitive or descriptive content that is empirically inaccurate and this inaccuracy is, in principle, available to objective, rational assessment. Our position responds to a popular view that, while some value judgments, such as racist judgments, might be abhorrent, values g...

We proffer the thesis that, in the process of defeating an inference on the basis of a factual truth that falsifies it, people move from a hypothetical truth-value to a factual truth-value of the conclusion. We will present evidence that shows (a) that some people spontaneously make a truth assumption and constrain their inferences to logically valid inferences, (b) that people tend to abandon ...

Social media could provide valuable information to support decision making in crisis management, such as in accidents, explosions and fires. However, much of the data from social media are images, which are uploaded in a rate that makes it impossible for human beings to analyze them. Despite the many works on image analysis, there are no fire detection studies on social media. To fill this gap,...

Spam is a never-ending issue that constantly consumes resources to no useful end. In this paper, we envision spam filtering as a pipeline consisting of DNS blacklists, filters based on SYN packet features, filters based on traffic characteristics and filters based on message content. Each stage of the pipeline examines more information in the message but is more computationally expensive. A mes...

In selective object segmentation, the goal is to extract the entire object of interest without regards to homogeneous regions or object shape. In this paper we present the selective image segmentation problem as a classification problem, and use active learning to train an image feature classifier to identify the object of interest. Since our formulation of this segmentation problem uses human ...

Ground truth is important not only for performance evaluation but also for a principled development of computer vision algorithms. Unfortunately obtaining ground truth data is difficult and often very labor intensive. This is particularly true of video analysis due to the immense cost of producing pixel-wise ground truth in potentially thousands of frames. In this paper, we propose a method to ...

Optical Music Recognition (OMR) has long been without an adequate dataset and ground truth for evaluating OMR systems, which has been a major problem for establishing a state of the art in the field. Furthermore, machine learning methods require training data. We analyze how the OMR processing pipeline can be expressed in terms of gradually more complex ground truth, and based on this analysis ...