Austin Hanson

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Traditional generative Markov random fields for segmenting images model the image data and corresponding labels jointly, which requires extensive independence assumptions for tractability. We present the conditional random field for an application in sign detection, using typical scale and orientation selective texture filters and a nonlinear texture(More)
This paper proposes a sophisticated classification process to segment the leaves of carrots from weeds. In the early stages of the plants' development, the color of both the plants and the weeds are similar, making it difficult to differentiate between the two. The process becomes even harder if the weeds and plants overlap. The proposed system addresses(More)
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