Image segmentation refers to a process of dividing
the image into disjoint regions that were
meaningful. This process is fundamental in computer
vision in that many applications, such as image
retrieval, visual summary, image based modeling, and
so on, can essentially benefit from it. This process
is also challenging because the segmentation is
usually subjective and the computation is highly
costly.
This book develops in turn the prior model for the
pairwise graph approaches which is defined from
multiple cues, a hyper graph based method which
models multiple wise relations among the data
points, and a tree structured graph based method
which leads to an efficient and effective solution
to the normalized cuts criterion. These approaches
are demonstrated in multiple view, interactive and
automatic image segmentation problems.
This book is suitable for students and researchers
in image processing, computer vision, pattern
recognition and machine learning.
Abstract Background: Fanconi anemia complementation group I (FANCI) acts as a critical protein factor for maintaining DNA stability. However, roles of FANCI in tumors has not been well revealed. In current study, we aimed to explore the function and potential mechanism of FANCI in non-small-cell lung cancer (NSCLC). Methods: To detect the expression of FANCI and UBE2T in NSCLC tissues, quantitative reverse-transcription PCR (qRT-PCR) and Western blot assays were employed. CCK-8, wound healing, Transwell, flow cytometry analysis and tumor xenograft were used to investigate the biological effects of FANCI in NSCLC in vitro and in vivo. FANCI binds with UBE2T was confirmed using coimmunoprecipitation (co-IP) assay. The EMT protein markers were detected via Western blot. Results: FANCI was upregulated in NSCLC tumor tissues compared with adjacent. In A549 and H1299 cells, knockdown of FANCI inhibited cell growth, migration, invasion and cell cycle,as well as epithelial-to-mesenchymal transition (EMT) in vitro. In vivo, the tumor growth was also repressed when FANCI was downregulated. Mechanistically, UBE2T directly bound with FANCI and regulated the monoubiquitination of FANCI. Futhermore, UBE2T restored the inhibitory effects induced by knocking down FANCI in NSCLC cells. Conclusion: FANCI was a putative oncogene in NSCLC, and was monouniubiquitinated by UBE2T to regulate cell growth, invasion and migration. Our findings suggested that FANCI might applied as a predicted biomarker and therapeutic target for NSCLC.
Sparse representation has been proved to be very efficient in machine learning and image processing. Traditional image sparse representation formulates an image into a one dimensional (1D) vector which is then represented by a sparse linear combination of the basis atoms from a dictionary. This 1D representation ignores the local spatial correlation inside one image. In this paper, we propose a two dimensional (2D) sparse model to much efficiently exploit the horizontal and vertical features which are represented by two dictionaries simultaneously. The corresponding sparse coding and dictionary learning algorithm are also presented in this paper. The 2D synthesis model is further evaluated in image denoising. Experimental results demonstrate our 2D synthesis sparse model outperforms the state-of-the-art 1D model in terms of both objective and subjective qualities.
In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra unlabeled data. We propose a novel consistency regularization approach, called cross pseudo supervision (CPS). Our approach imposes the consistency on two segmentation networks perturbed with different initialization for the same input image. The pseudo one-hot label map, output from one perturbed segmentation network, is used to supervise the other segmentation network with the standard cross-entropy loss, and vice versa. The CPS consistency has two roles: encourage high similarity between the predictions of two perturbed networks for the same input image, and expand training data by using the unlabeled data with pseudo labels. Experiment results show that our approach achieves the state-of-the-art semi-supervised segmentation performance on Cityscapes and PASCAL VOC 2012.
This paper takes the literature related to the computer engineering practice training mode on CNKI as a sample, conducts a quantitative analysis of the literature from the dimensions of high-impact authors, high-frequency keywords, and time-space distribution, sorts out the research context of my country's engineering practice training mode, and reveals this field.The research hotspots and research trends of this paper provide a reference for the further development of related research on the engineering practice training mode of computer courses.
The decay of litter in the air (that is, standing litter) and on the ground is an essential process of litter decomposition for many plant species. However, the contribution of standing litter to litter decomposition (e.g., CO 2 emission) is still ambiguous, especially for non-leaf litter. In this study, we examined the CO 2 emission from reed litter ( Phragmites communis ) in coastal wetlands in the Yellow River Delta (YRD), China. The results showed that the soil litter released more CO 2 than the standing litter due to its rapid loss of labile organic carbon and high enzyme activities (that is, invertase and β-glucosidase). In contrast, cumulative CO 2 emissions from standing litter were equivalent to 56%–70% of those on the soil surface, indicating that CO 2 emissions from standing litter cannot be ignored. The sheath litter had the highest cumulative CO 2 emission per unit of dry biomass among the three types of litter. Taking into account the biomass per unit area, the non-leaf litter (that is, culm and sheath) emitted more CO 2 than leaf litter. On the daily scale, the litter released more CO 2 at night than in the daytime, because low air temperature and high relative air humidity at night can help dew formation, accelerating CO 2 emission at night. On the seasonal scale, air temperature and relative air humidity were positively related to CO 2 emission, leading to rapid CO 2 emission in summer and fall. The Q 10 value of CO 2 emission from standing litter (an average of 1.44) was lower than that of litter on the ground (an average of 2.16) due to a low residual rate of recalcitrant organic carbon in standing litter. Our findings highlight that standing litter decomposition should not be overlooked and suggest that more attention should be paid to the decay of non-leaf litter in the coastal wetland of the YRD.
The network communication is realized and developed based on the gradual improvement of the computer network. Although the communication system itself is not equivalent to the computer network, but there are many integration and connection in current communication system and the computer network, which has formed a complementary and mutual development of the situation. With the emergence and application of new systems and computer network technologies, such integration and development will be more in-depth and closer. This article is focus on the computer network and the communication system, and does a brief analysis of the status quo, so that it is easy to understand by the majority of readers in the shallow level.
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