Coarse-level object recognition using interlevel products of complex wavelets

This paper introduces the Interlevel Product (ILP) which is a transform based upon the Dual-Tree Complex Wavelet. Coefficients of the ILP have complex values whose magnitudes indicate the amplitude of multilevel features, and whose phases indicate the nature of these features (e.g. ridges vs. edges). In particular, the phases of ILP coefficients are approximately invariant to small shifts in the original images. We accordingly introduce this transform as a solution to coarse scale template matching, where alignment concerns between decimation of a target and decimation of a larger search image can be mitigated, and computational efficiency can be maintained. Furthermore, template matching with ILP coefficients can provide several intuitive "near-matches" that may be of interest in image retrieval applications. © 2005 IEEE.

Semantic Discriminant mapping for classification and browsing of remote sensing textures and objects

We present a new approach based on Discriminant Analysis to map a high dimensional image feature space onto a subspace which has the following advantages: 1. each dimension corresponds to a semantic likelihood, 2. an efficient and simple multiclass classifier is proposed and 3. it is low dimensional. This mapping is learnt from a given set of labeled images with a class groundtruth. In the new space a classifier is naturally derived which performs as well as a linear SVM. We will show that projecting images in this new space provides a database browsing tool which is meaningful to the user. Results are presented on a remote sensing database with eight classes, made available online. The output semantic space is a low dimensional feature space which opens perspectives for other recognition tasks. © 2005 IEEE.

榕母管蓟马生物学特性研究

研究了榕母管蓟马（ＧｙｎａｉｋｏｔｈｒｉｐｓｕｚｅｌｉＺｉｍｍｅｒｍａｎ）生物学特性，结果表明：在温度２７、３０℃时，正常羽化率达９０．０％～９５．０％，雌虫产卵量达７５～８０粒，卵的孵化率达９０．０％～１００％。在２４℃温度范围内，成虫寿命长达３０～５６ｄ。在云南景谷１年发生８代，世代重叠。

Restoration of images and 3D data to higher resolution by deconvolution with sparsity regularization

Image convolution is conventionally approximated by the LTI discrete model. It is well recognized that the higher the sampling rate, the better is the approximation. However sometimes images or 3D data are only available at a lower sampling rate due to physical constraints of the imaging system. In this paper, we model the under-sampled observation as the result of combining convolution and subsampling. Because the wavelet coefficients of piecewise smooth images tend to be sparse and well modelled by tree-like structures, we propose the L0 reweighted-L2 minimization (L0RL2 ) algorithm to solve this problem. This promotes model-based sparsity by minimizing the reweighted L2 norm, which approximates the L0 norm, and by enforcing a tree model over the weights. We test the algorithm on 3 examples: a simple ring, the cameraman image and a 3D microscope dataset; and show that good results can be obtained. © 2010 IEEE.

Convex approaches to model wavelet sparsity patterns

Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as deconvolution, tomography, and compressed sensing, the presence of a sensing or observation matrix produces a linear mixing of the simple Markovian dependency structure. This leads to reconstruction problems that are non-convex optimizations. Past work has dealt with this issue by resorting to greedy or suboptimal iterative reconstruction methods. In this paper, we propose new modeling approaches based on group-sparsity penalties that leads to convex optimizations that can be solved exactly and efficiently. We show that the methods we develop perform significantly better in de-convolution and compressed sensing applications, while being as computationally efficient as standard coefficient-wise approaches such as lasso. © 2011 IEEE.

Biologically-inspired object recognition system with features from complex wavelets

In this paper, a novel cortex-inspired feed-forward hierarchical object recognition system based on complex wavelets is proposed and tested. Complex wavelets contain three key properties for object representation: shift invariance, which enables the extraction of stable local features; good directional selectivity, which simplifies the determination of image orientations; and limited redundancy, which allows for efficient signal analysis using the multi-resolution decomposition offered by complex wavelets. In this paper, we propose a complete cortex-inspired object recognition system based on complex wavelets. We find that the implementation of the HMAX model for object recognition in [1, 2] is rather over-complete and includes too much redundant information and processing. We have optimized the structure of the model to make it more efficient. Specifically, we have used the Caltech 5 standard dataset to compare with Serre's model in [2] (which employs Gabor filter bands). Results demonstrate that the complex wavelet model achieves a speed improvement of about 4 times over the Serre model and gives comparable recognition performance. © 2011 IEEE.

Co-occurrence flow for pedestrian detection

The last few years have seen considerable progress in pedestrian detection. Recent work has established a combination of oriented gradients and optic flow as effective features although the detection rates are still unsatisfactory for practical use. This paper introduces a new type of motion feature, the co-occurrence flow (CoF). The advance is to capture relative movements of different parts of the entire body, unlike existing motion features which extract internal motion in a local fashion. Through evaluations on the TUD-Brussels pedestrian dataset, we show that our motion feature based on co-occurrence flow contributes to boost the performance of existing methods. © 2011 IEEE.

底栖动物估算扁担塘和后湖的渔产潜力

扁担塘、后湖大型底栖动物代表水丝蚓、铜锈环棱螺对红鲤的平均饵料系数(湿重)分别为6.2、31.3。据此估算的理论渔业增产潜力分别是:扁担塘底栖动物的渔产潜力为4 259.83 kg/hm2,后湖底栖动物的渔产潜力为4 825.78 kg/hm2。后湖底栖动物的生产量和渔产潜力均比扁担塘的要高。

沉积物与悬浮物中磷分级分离形态差异的初步研究

以滇池2个典型的严重富营养化湖湾———马村湾和海东湾为研究区域,研究分析了2个湖湾沉积物及水体悬浮物中4种磷的赋存形态:松散吸附态磷(NH4Cl-P)、氧化还原敏感态磷(BD-P)、金属结合态磷(NaOH-P)和钙结合态磷(HCl-P)以及有机质含量及总磷(TP)含量.结果表明:沉积物随着风浪搅动悬浮进入水体后,4种形态的磷含量及其所占总磷的比例均发生了较大变化,NH4Cl-P的含量升高,是由于快速的吸附作用所致;NaOH-P在4种磷形态中的比例下降,含量上升,表明沉积物再悬浮进入水体后磷的活化特性加大,

phbB基因在莱茵衣藻中的表达与分子检测

通过构建依赖NADPH的乙酰乙酰CoA还原酶基因(phbB)的衣藻表达载体, 用石英砂VOTEX转化技术, 将phbB基因导入细胞壁缺陷的莱茵衣藻(Chlamydomonas reinhardtii cc-849)中, 用含有10 mg/mL的Zeomycin的平板培养基进行筛选和实验室保持培养, 得到了表达phbB基因的转基因藻株. PCR和Southern blot结果显示phbB基因已整合到莱茵衣藻基因组中. RT-PCR与DNA杂交的检测结果显示, 导入的phbB基因在衣藻中具有转录活性.

Synthesis and structures of morphology-controlled ZnO nano- and microcrystals

Zinc oxide flower-like bunches were directly synthesized on indium-doped tin oxide (ITO) glass substrates through a simple chemical bath deposition process. By adjusting precursor concentration, other morphologies ( spindles and rods) were also obtained. All of them are hexagonal and single crystalline in nature and grow along the [ 0001] crystallographic direction. The possible growth mechanisms for these nano- and microcrystals were proposed. It was revealed that both the inherent highly anisotropic structure of ZnO and the precursor concentration play crucial roles in determining final morphologies of the products. In addition, vibrational properties of ZnO crystals with different morphologies were investigated by Raman spectroscopy.