Interpreting Images

Just as it’s possible to understand novel sentences without having heard them before, it’s possible to understand novel pictures without having seen them before. But these possibilities are often supposed to have totally different explanations: whereas the ability to understand novel sentences is supposed to be explained by tacit knowledge of a compositional theory of meaning for their language, the ability to understand novel pictures is supposed to be explained differently. In this paper I argue against this disanalogy: insofar as the ability to understand novel sentences is explained by tacit knowledge of a compositional theory, I argue, so is the ability to understand novel pictures

Looking at the Lanham Act: Images in Trademark and Advertising Law

Words are the prototypical regulatory subjects for trademark and advertising law, despite our increasingly audiovisual economy. This word-focused baseline means that the Lanham Act often misconceives its object, resulting in confusion and incoherence. This Article explores some of the ways courts have attempted to fit images into a word-centric model, while not fully recognizing the particular ways in which images make meaning in trademark and other forms of advertising. While problems interpreting images are likely to persist, this Article suggests some ways in which courts could pay closer attention to the special features of images as compared to words

A mosaic of eyes

Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties

Students' Ability To Interpret Pattern Imagessocial Cultural Spatial Of The Google Maps Application

Spatial pattern material in learning requires strong visualization so that students can understand complex concepts. However, the use of conventional media that does not support interactive visualization can make it difficult for students to understand the material and develop interpretation skills. This research aims to overcome this problem by using the Google Maps application in interpreting images of socio-cultural spatial patterns for students at SMA Negeri 1 Kalianda.The research was conducted in class The research results showed that 33 students or 94.29% could use the Google Maps application very well, 29 students or 82.86% were able to interpret the spatial patterns around their respective students' residences, 28 students or 80% were able to interpret socio-cultural spatial characteristics , and 30 students or 85.71% were able to conclude the spatial pattern of their area.Thus, the use of the Google Maps application in interpreting images of socio-cultural spatial patterns has the potential to improve students' ability to interpret spatial patterns that are spread out, clustered and elongated, but further efforts are still needed to increase the number of students who achieve adequate interpreting criteria. This research has implications that learning approaches involving interactive applications such as Google Maps can be an effective alternative in developing students' interpreting skills in the field of geography

Miracle of imaging: the truth is out there!

Introduction In medical practice, we encounter many diseases, which can manifest in different ways. Most of the time, careful history taking and meticulous clinical examination can easily direct the clinician towards an accurate diagnosis. While with others, they may need further supporting evidence either from laboratory investigations or imaging. Likewise, the radiologists face daily challenges of analyzing and interpreting high volume of images in a timely manner. Appropriate diagnosis or differential diagnosis can be derived from cases with good clinical correlation. However, it can be misleading for the radiologists when interpreting images in cases where the history or clinical presentation is unclear although meticulous image assessment for high quality diagnostic and patient care are indeed paramount. Case series We retrospectively reviewed cases where discrepancies existed between the indications for the imaging with findings detected during these investigations. The subsequent management or outcome of the patients is briefly described. Conclusion Thorough history and good clinical assessment can guide radiologists in the analysis and interpretation of the radiological images in most patients. Our illustration of cases will be a good reminder for radiologists to always be meticulous when interpreting images to minimize errors or missed abnormalities as misleading history or clinical presentation is bound to happen

Introduction to Magnetic Resonance Imaging Techniques

It is quite possible to acquire images with an MR scanner without understanding the principles behind it, but choosing the best parameters and methods, and interpreting images and artifacts, requires understanding. This text serves as an introduction to magnetic resonance imaging techniques. It is aimed at beginners in possession of only a minimal level of technical expertise, yet it introduces aspects of MR that are typically considered technically challenging. The notes were written in connection with teaching of audiences with mixed backgrounds

Relationship Between Two Generalized Images for Discrete and Differential Camera Motions

The recent popularity of catadioptic and multi-camera imaging systems indicates a need to create formal models for general, non-perspective camera geometries. Development of algorithmic tools for interpreting images from a generalized camera model will lead to a better understanding of how to design camera systems for particular tasks. Here we define the corollary to epi-polar constraints for standard cameras - the relationship between two images of a scene taken by generalized cameras from viewpoints related by discrete or differential motions