We present a simple and effective method for 3D hand pose estimation from a single depth frame. As opposed to previous state-of-the-art methods based on holistic 3D regression, our method works on dense pixel-wise estimation. This is achieved by careful design choices in pose parameterization, which leverages both 2D and 3D properties of depth map. Specifically, we decompose the pose parameters...

A common approach to solving multi-label learning problems is to use problem transformation methods and dichotomizing classifiers as in the pair-wise decomposition strategy. One of the problems with this strategy is the need for querying a quadratic number of binary classifiers for making a prediction that can be quite time consuming, especially in learning problems with a large number of label...

Single cell segmentation is critical and challenging in live cell imaging data analysis. Traditional image processing methods and tools require time-consuming and labor-intensive efforts of manually fine-tuning parameters. Slight variations of image setting may lead to poor segmentation results. Recent development of deep convolutional neural networks(CNN) provides a potentially efficient, gene...

It has been shown that the alternating direction method of multipliers (ADMM) is not necessarily convergent when it is directly extended to a multiple-block linearly constrained convex minimization model with an objective function in the sum of more than two functions without coupled variables. Most recently, we proposed the block-wise ADMM, which was obtained by regrouping the variables and fu...

A shortcut procedure as quick, easy-to use method for design and simulation of multicomponent batch distillation is used to predict the operating condition of recovering xylene from solvent in an existing batch distillation column in benzol refinery. The procedure can be used to investigate the effect of the operating parameters on the operation of column for three possible modes of batch d...