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A full-length abscisic acid (ABA) senescence and ripening inducible gene named LcAsr was obtained from litchi. Bioinformatic analysis showed that full-length LcAsr was 1,177 bp and contained an open reading frame (ORF) encoding 153 amino acids, 85- and 146-bp 5′ and 3′ UTRs, respectively. LcAsr was expressed in all organs, with preferential expression in(More)
Centralized charging of electric vehicles (EVs) based on battery swapping is a promising strategy for their large-scale utilization in power systems. The most outstanding feature of this strategy is that EV batteries can be replaced within a short time and can be charged during off-peak periods or on low electric price and scheduled in any battery swap(More)
Robust scale calculation is a challenging problem in visual tracking. Most existing trackers fail to handle large scale variations in complex videos. To address this issue, we propose a robust and efficient scale calculation method in tracking-by-detection framework, which divides the target into four patches and computes the scale factor by finding the(More)
During the last years, Automatic video analysis has become a very important research for video management, such as video index and video retrieval. The application domains are disparate, ranging from video surveillance to automatic video annotation for sport videos or TV shots. Whatever the application field, most of the works in video analysis are based on(More)
Content-based image retrieval (CBIR) is an effective approach for obtaining desired image, however, due to the semantic gap between low-level visual features and high-level concept of image, CBIR system of state-of-the-art always can’t achieve satisfying retrieval performance. In this paper, we propose a novel CBIR system framework. In order to(More)
Night image enhancement is an active research area nowadays. There have been a lot of techniques proposed in this area. In this paper, we present a contrast enhancement method base on Adaptive Dynamic Histogram Equalization (ADHE) for night vision image. The ADHE firstly decomposed an input image into two subimages based on the energy threshold of the input(More)
—By improving the local contrast between targets and background in the static infrared images, a simple and effective background model is proposed to detect targets. At the same time, a novel learning algorithm is presented for training a discriminatively trained, part-based model with only positives images, for pedestrian recognition. The background models(More)
For large-scale image retrieval, high dimensional features make the retrieval system inefficiency. In this paper, we propose a framework of deep feature hash codes for content-based image retrieval system. In this framework, we firstly extract image features by a pre-trained convolutional neural networks model. Secondly, we use different hashing methods for(More)