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Using Bag of Words Approach for Classifying Native Arizona Snakes in Images as Venomous or Non-Venomous

Description
Uninformed people frequently kill snakes without knowing whether they are venomous or harmless, fearing for their safety. To prevent unnecessary killings and to encourage people to be safe around venomous snakes, a proper identification is important. This work seeks to preserve wild native Arizona snakes and promote a general interest…

Uninformed people frequently kill snakes without knowing whether they are venomous or harmless, fearing for their safety. To prevent unnecessary killings and to encourage people to be safe around venomous snakes, a proper identification is important. This work seeks to preserve wild native Arizona snakes and promote a general interest in them by using a bag of features approach for classifying native Arizona snakes in images as venomous or non-venomous. The image category classifier was implemented in MATLAB and trained on a set of 245 images of native Arizona snakes (171 non-venomous, 74 venomous). To test this approach, 10-fold cross-validation was performed and the average accuracy was 0.7772. While this approach is functional, the results could be improved, ideally with a higher average accuracy, in order to be reliable. In false positives, the features may have been associated with the color or pattern, which is similar between venomous and non-venomous snakes due to mimicry. Polymorphic traits, color morphs, variation, and juveniles that may exhibit different colors can cause false negatives and misclassification. Future work involves pre-training image processing such as improving the brightness and contrast or converting to grayscale, interactively specifying or generating regions of interest for feature detection, and targeting reducing the false negative rate and improve the true positive rate. Further study is needed with a larger and balanced image set to evaluate its performance. This work may potentially serve as a tool for herpetologists to assist in their field research and to classify large image sets.
ContributorsIp, Melissa A (Author) / Li, Baoxin (Thesis director) / Chandakkar, Parag (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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The reality of directed forgetting in the item-method paradigm: suppression, not selective search or decay

Description
It has been suggested that directed forgetting (DF) in the item-method paradigm results from selective rehearsal of R items and passive decay of F items. However, recent evidence suggested that the passive decay explanation is insufficient. The current experiments examined two theories of DF that assume an active forgetting process:…

It has been suggested that directed forgetting (DF) in the item-method paradigm results from selective rehearsal of R items and passive decay of F items. However, recent evidence suggested that the passive decay explanation is insufficient. The current experiments examined two theories of DF that assume an active forgetting process: (1) attentional inhibition and (2) tagging and selective search (TSS). Across three experiments, the central tenets of these theories were evaluated. Experiment 1 included encoding manipulations in an attempt to distinguish between these competing theories, but the results were inconclusive. Experiments 2 and 3 examined the theories separately. The results from Experiment 2 supported a representation suppression account of attentional inhibition, while the evidence from Experiment 3 suggested that TSS was not a viable mechanism for DF. Overall, the results provide additional evidence that forgetting is due to an active process, and suggest this process may act to suppress the representations of F items.
ContributorsHansen, Whitney Anne (Author) / Goldinger, Stephen D. (Thesis advisor) / Azuma, Tamiko (Committee member) / Brewer, Gene (Committee member) / Homa, Donald (Committee member) / Arizona State University (Publisher)
Created2011