AbdulWahab Kabani

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We describe a deep learning model that can be used to recognize individual right whales in aerial images. We developed our model using a data set provided by the National Oceanic and Atmospheric Administration. The main challenge we faced when working on this data set is that the size of the training set is very small (4,544 images) with some classes having(More)
We present a fully automated method to estimate the ejection fraction, the end-systolic and end-diastolic volumes from cardiac MRI images. These values can be manually measured by a cardiologist but the process is slow and time consuming. The method is based on localizing the left ventricle of the image. Then, the slices are cleaned, re-ordered, and(More)
Right Whales can be recognized by the callosities pattern on their heads. They are an endangered species with an estimated 450 whales remaining. Marine biologists regularly perform manual recognition of the whales while monitoring the population but the process is slow and time consuming. Deep learning methods achieved state-of-the-art results on several(More)
In this paper, we present an image compression algorithm called Weighted, Ratio-Based, Adaptive, Lossless image Codec (WRALIC). The algorithm utilizes 5 ratio predictions. The weight of each prediction is learned during a training stage offline, whereas the prediction parameters are adjusted using error context. The absolute value of the error is encoded.(More)
Existing work on gait recognition is focused on casual (western) customs hence not suitable for the Gulf region where long gowns are used for both men and women. This paper proposes a gait recognition solution that is suitable for both Gulf customs and casual customs. The solution is based on computing an adaptive image prediction between consecutive(More)
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