![]() ![]() Though some structural differences may exist, these are imperceptible to the human eye since it focusses on “what it wants to see.” This is the central idea behind our work that trains a deep convolutional neural network on commonly found natural scene images containing visual structures similar in appearance to cropped images of pulmonary nodules from computed tomography (CT) scans for the purpose of cancer diagnosis. The Gestalt principle of similarity states that the human mind tends to club visually similar structures together based on some object attributes such as shape and color. We specifically focus on the pulmonary nodule detection problem in which the task is to distinguish the image patches that contain lung nodules from those that do not. In the distant domain problem addressed in this paper, the source and target domains are totally unrelated but have similar visual structures, thereby infusing explainability in transfer learning. This research is important, considering the number of very high-profile cases in the last few decades in which young Blacks were killed by people who claimed to believe that the unarmed individuals were armed and/or represented some threat to their personal safety.Transfer learning is a trending concept in computer vision that is based on the transfer of knowledge between the source and target domains. Furthermore, White individuals’ decisions to shoot an armed target in a video game is made more quickly when the target is Black (Correll, Park, Judd, & Wittenbrink, 2002 Correll, Urland, & Ito, 2006). For instance, several studies have demonstrated that non-Black participants identify weapons faster and are more likely to identify non-weapons as weapons when the image of the weapon is paired with the image of a Black person (Payne, 2001 Payne, Shimizu, & Jacoby, 2005). Research suggests that implicit racial prejudice and stereotypes affect perception. Built from sensations, but influenced by our own experiences, biases, prejudices, and cultures, perceptions can be very different from person to person. In this module, you have learned that perception is a complex process. Presumably, our ability to interpret sensory information depends on what we label as figure and what we label as ground in any particular case, although this assumption has been called into question (Peterson & Gibson, 1994 Vecera & O’Reilly, 1998).ĭig Deeper: The Depths of Perception: Bias, Prejudice, and Cultural Factors ![]() As Figure 1 shows, our perception can vary tremendously, depending on what is perceived as figure and what is perceived as ground. Figure is the object or person that is the focus of the visual field, while the ground is the background. According to this principle, we tend to segment our visual world into figure and ground. One Gestalt principle is the figure-ground relationship. As a result, Gestalt psychology has been extremely influential in the area of sensation and perception (Rock & Palmer, 1990). Gestalt psychologists translated these predictable ways into principles by which we organize sensory information. In other words, the brain creates a perception that is more than simply the sum of available sensory inputs, and it does so in predictable ways. The word gestalt literally means form or pattern, but its use reflects the idea that the whole is different from the sum of its parts. This belief led to a new movement within the field of psychology known as Gestalt psychology. Wertheimer, and his assistants Wolfgang Köhler and Kurt Koffka, who later became his partners, believed that perception involved more than simply combining sensory stimuli. In the early part of the 20th century, Max Wertheimer published a paper demonstrating that individuals perceived motion in rapidly flickering static images-an insight that came to him as he used a child’s toy tachistoscope. ![]()
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