No abstract

Identifying individual animals is crucial for many biological investigations. In response to some of the limitations of current identification methods, new automated computer vision approaches have emerged with strong performance. Here, we review current advances of computer vision identification techniques to provide both computer scientists and biologists with an overview of the available tools and discuss their applications. We conclude by offering recommendations for starting an animal identification project, illustrate current limitations and propose how they might be addressed in the future.

Multiple responses to a configurational sample stimulus were obtained from five male aphasic patients. Through this technique, it was possible to obtain a stop-motion view of perceptual skills and cognitive functions.

The ability of 24 aphasics to make the perceptualdiscriminations, presumed to be basic to reading, was assessed and trained in automated fashion. Five training programs utilized forms abstracted as those necessary to compose the symbols of the English (Modern European) alphabet, and employed them in shape, up-down, and right-left discrimination tasks. A verbal transfer test was composed of sets of words, nonsense syllables, and individual letters. Data from the aphasic patients indicated that the training programs were effective in improving the latency of the discrimination response and that this improvement was manifested in general transfer to verbal test items. Training and transfer gains were maintained for at least a week after training. The results are interpreted as offering support for the view that form discrimination is a basic factor in at least the visual verbal aspect of language behavior. They also indicate that it is possible to design effective automated training procedures for use with patients who have frequently been considered untrainable.

Five aphasics and five controls were compared in their response to three perceptual discrimination programs presented in automated fashion. The programs, composed of shapes based upon those necessary to form English capital letters, were concerned with the variables of shape discrimination, orientation of form, and transition of solid shape to outline figure. Aphasics and controls differed significantly in response latencies and error rates to sets of pre-test items representing each program. Aphasics were given automated training with those programs on whose pre-test they had an error rate greater than 10%. On follow-up testing one week after training, response latency decreased and differed significantly from pre-test latency, and the error rate became comparable to that of the normal controls.