Baojie Fan

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This paper proposes a method for the job shop scheduling problem (JSSP) based on the hybrid metaheuristic method. This method makes use of the merits of an improved particle swarm optimization (PSO) and a tabu search (TS) algorithm. In this work, based on scanning a valuable region thoroughly, a balance strategy is introduced into the PSO for enhancing its(More)
In this paper, we focus on unsupervised feature selection. As we have known, the combination of several feature units into a whole feature vector is broadly adopted for effective object representation, which may inevitably includes some irrelevant/redundant feature units or feature dimensions. Most of the traditional feature selection models can only select(More)
In this paper, a supervised approach to online learn a structured sparse and discriminative representation for object tracking is presented. Label information from training data is incorporated into the dictionary learning process to construct a compact and discriminative dictionary. This is accomplished by adding an ideal-code regularization term and(More)
A robust progressive structure from motion (PSFM) method is proposed for unordered images. Our method can reduce accumulative error efficiently during scene dense recovery and camera motion estimation. The whole unordered images are divided into two classes: key frames and non-key frames. For key frames, superior features are selected and tracked to(More)
Mungbean (Vigna radiata L. Wilczek) is one of the most important leguminous food crops in Asia. We employed Illumina paired-end sequencing to analyse transcriptomes of three different mungbean genotypes. A total of 38.3–39.8 million paired-end reads with 73 bp lengths were generated. The pooled reads from the three libraries were assembled into 56,471(More)
Active Contour can describe targets accurately and has been widely used in image segmentation and target tracking. Its main drawback is huge computation that is still not well resolved. In this paper, by analyzing curve gradient flow, the evolution of active contour is divided into two steps: global translation and local deformation. When the curve is far(More)