Chun-Shun Tseng

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⎯This paper presents an improved multi-object segmentation algorithm based on probabilistic labeling. First, a critical look is focused on utilizing vector calculus operator and combinational operator to rewrite Dirichlet integral into a matrix form, and boundary condition is defined to obtain the needed harmonic function. The only unique parameter β that(More)
—This paper presents an eavesdropper-proof algorithm that is capable of fast generating symmetric (secret) keys. Instead of literally exchanging secret keys, both the sender and receiver adopt a mirroring process based on an improved Hebbian rule that uses identical random inputs to separately train on their reciprocal outputs to generate a pair of exactly(More)
This paper presents a self-organizing fusion neural network (SOFNN) which is effective in performing fast image segmentation. Based on a counteracting learning strategy, SOFNN employs two parameters that together control the learning rate in a counteracting manner to achieve free of over-segmentation and under-segmentation. Regions comprising an object are(More)
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