ClassCut for Unsupervised Class Segmentation

Abstract. We propose a novel method for unsupervised class segmentation on a set of images. It alternates between segmenting object instances and learning a class model. The method is based on a segmentation energy defined over all images at the same time, which can be optimized efficiently by techniques used before in interactive segmentation. Over iterations, our method progressively learns a class model by integrating observations over all images. In addition to appearance, this model captures the location and shape of the class with respect to an automatically determined coordinate frame common across images. This frame allows us to build stronger shape and location models, similar to those used in object class detection. Our method is inspired by interactive segmentation methods [1], but it is fully automatic and learns models characteristic for the object class rather than specific to one particular object/image. We experimentally demonstrate on the Caltech4, Caltech101, and Weizmann horses datasets that our method (a) transfers class knowledge across images and this improves results compared to segmenting every image independently; (b) outperforms Grabcut [1] for the task of unsupervised segmentation; (c) offers competitive performance compared to the state-of-the-art in unsupervised segmentation and in particular it outperforms the topic model [2].

Political Corruption and Corporate Risk-Taking

We use variation in corruption convictions across judicial districts in the US to examine the relationship between political corruption and risk-taking of public firms. Firms headquartered in regions with high levels of political corruption have lower total risk and lower idiosyncratic risk on average. Further analysis shows that corruption tends to encourage firms to pursue risk-decreasing investments, lower the riskiness of their operations, and decrease asset liquidity. While managerial ownership is intended to align the interests of managers and shareholders, the presence of corruption appears to encourage undiversified managers to decrease risk-taking. Our evidence is consistent with agency theory and the asset-shielding argument that political corruption discourages managers from taking risks that expose firms to expropriation by politicians, resulting in suboptimal corporate policies

Minimal Obstructions for Partial Representations of Interval Graphs

Interval graphs are intersection graphs of closed intervals. A generalization of recognition called partial representation extension was introduced recently. The input gives an interval graph with a partial representation specifying some pre-drawn intervals. We ask whether the remaining intervals can be added to create an extending representation. Two linear-time algorithms are known for solving this problem. In this paper, we characterize the minimal obstructions which make partial representations non-extendible. This generalizes Lekkerkerker and Boland's characterization of the minimal forbidden induced subgraphs of interval graphs. Each minimal obstruction consists of a forbidden induced subgraph together with at most four pre-drawn intervals. A Helly-type result follows: A partial representation is extendible if and only if every quadruple of pre-drawn intervals is extendible by itself. Our characterization leads to a linear-time certifying algorithm for partial representation extension

Improved detection of air-filled lesions using computed tomography in dogs with recurrent spontaneous pneumothorax through reduction of pulmonary atelectasis via positive pressure ventilation

IntroductionSpontaneous pneumothorax in dogs is predominantly caused by the rupture of air-filled lesions, such as bullae or blebs. The efficacy of Computed Tomography (CT) in detecting these lesions has been deemed limited due to its reportedly low sensitivity. This retrospective, cross-sectional study investigates the utility of CT in eight dogs diagnosed with recurrent pneumothorax, all of which had surgical confirmation of the cause of the pneumothorax.Materials and methodsThoracic radiographs were obtained before and the day following the CT studies. Initially, a CT study was conducted without positive pressure ventilation (pre-PPV CT). Subsequent CT studies were performed post-evacuation of pneumothorax and with positive pressure ventilation of 15 cmH2O until lung atelectasis was resolved (post-PPV CT). The pre-PPV CT and post-PPV CT images were anonymized and reviewed by two board-certified radiologists. The presence and morphology of air-filled lesions were evaluated on all images. Surgical findings were recorded and compared to the CT findings.ResultsAir-filled lesions were detected in 5 out of 8 dogs in the pre-PPV CT studies and in all 8 dogs in the post-PPV CT studies. The CT findings of air-filled lesions were consistent with surgical findings. None of the dogs showed increased severity of pneumothorax in radiographs taken the day following the CT studies.DiscussionsThe study concludes that the resolution of lung atelectasis by evacuation of pneumothorax and positive pressure ventilation during CT studies is feasible and enhances the detection of air-filled lesions in dogs with recurrent spontaneous pneumothorax. This could potentially aid in improving surgical planning

On strongly chordal graphs that are not leaf powers

A common task in phylogenetics is to find an evolutionary tree representing proximity relationships between species. This motivates the notion of leaf powers: a graph G = (V, E) is a leaf power if there exist a tree T on leafset V and a threshold k such that uv is an edge if and only if the distance between u and v in T is at most k. Characterizing leaf powers is a challenging open problem, along with determining the complexity of their recognition. This is in part due to the fact that few graphs are known to not be leaf powers, as such graphs are difficult to construct. Recently, Nevries and Rosenke asked if leaf powers could be characterized by strong chordality and a finite set of forbidden subgraphs. In this paper, we provide a negative answer to this question, by exhibiting an infinite family \G of (minimal) strongly chordal graphs that are not leaf powers. During the process, we establish a connection between leaf powers, alternating cycles and quartet compatibility. We also show that deciding if a chordal graph is \G-free is NP-complete, which may provide insight on the complexity of the leaf power recognition problem

CPU, GPU i FPGA implementacija MALD algoritma za otkrivanje nepravilnosti na površini keramičkih pločica

This paper addresses adjustments, implementation and performance comparison of the Moving Average with Local Difference (MALD) method for ceramic tile surface defects detection. Ceramic tile production process is completely autonomous, except the final stage where human eye is required for defects detection. Recent computational platform development and advances in machine vision provides us with several options for MALD algorithm implementation. In order to exploit the shortest execution time for ceramic tile production process, the MALD method is implemented on three different platforms: CPU, GPU and FPGA, and it is implemented on each platform in at least two ways. Implementations are done in MATLAB’s MEX/C++, C++, CUDA/C++, VHDL and Assembly programming languages. Execution times are measured and compared for different algorithms and their implementations on different computational platforms.U ovom radu razmatra se prilagodba, implementacija i usporedba performansi metode pomičnog usrednjavanja s lokalnom diferencijom (MALD) s primjenom u otkrivanju površinskih nedostataka na keramičkim pločicama. Proizvodna linija keramičkih pločica je autonomna sve do zadnje faze u kojoj je potreban ljudski vid kako bi se otkrili eventualni nedostaci na keramičkim pločicama. Nedavnim razvojem računalnih platformi i razvojem metoda računalnog vida omogućena je implementacija MALD metode na nekoliko načina. U nastojanju skraćenja vremena potrebnog za proizvodnju keramičkih pločica, MALD metoda je implementirana u trima različitim platformama: CPU (central processing unit), GPU (graphic processing unit) i FPGA (field programmable gate array), te s barem dva različita algoritma. Implementacija je izvršena sa MATLAB MEX/C++, C++, CUDA/C++, VHDL te Asembler programskim jezicima. Izmjerena vremena obrade su me.usobno uspore.ena za različite algoritme i njihove implementacije na različitim računalnim platformama

Minimising the number of gap-zeros in binary matrices

We study a problem of minimising the total number of zeros in the gaps between blocks of consecutive ones in the columns of a binary matrix by permuting its rows. The problem is referred to as the Consecutive Ones Matrix Augmentation Problem, and is known to be NP-hard. An analysis of the structure of an optimal solution allows us to focus on a restricted solution space, and to use an implicit representation for searching the space. We develop an exact solution algorithm, which is linear-time in the number of rows if the number of columns is constant, and two constructive heuristics to tackle instances with an arbitrary number of columns. The heuristics use a novel solution representation based upon row sequencing. In our computational study, all heuristic solutions are either optimal or close to an optimum. One of the heuristics is particularly effective, especially for problems with a large number of rows

Understanding edge-connectivity in the Internet through core-decomposition

Internet is a complex network composed by several networks: the Autonomous Systems, each one designed to transport information efficiently. Routing protocols aim to find paths between nodes whenever it is possible (i.e., the network is not partitioned), or to find paths verifying specific constraints (e.g., a certain QoS is required). As connectivity is a measure related to both of them (partitions and selected paths) this work provides a formal lower bound to it based on core-decomposition, under certain conditions, and low complexity algorithms to find it. We apply them to analyze maps obtained from the prominent Internet mapping projects, using the LaNet-vi open-source software for its visualization

An ultrasound based platform for image-guided radiotherapy in canine bladder cancer patients

Background and purpose: Ultrasound (US) is a non-invasive, non-radiographic imaging technique with high spatial and temporal resolution that can be used for localizing soft-tissue structures and tumors in real-time during radiotherapy (RT) (inter- and intra-fraction). A comprehensive approach incorporating an in-house 3D-US system within RT is presented. This system is easier to adopt into existing treatment protocols than current US based systems, with the aim of providing millimeter intra-fraction alignment errors and sensitivity to track intra-fraction bladder movement. Materials and methods: An in-house integrated US manipulator and platform was designed to relate the computed tomographic (CT) scanner, 3D-US and linear accelerator coordinate systems. An agar-based phantom with measured speed of sound and densities consistent with tissues surrounding the bladder was rotated (0-45°) and translated (up to 55 mm) relative to the US and CT coordinate systems to validate this device. After acquiring and integrating CT and US images into the treatment planning system, US-to-US and US-to-CT images were co-registered to re-align the phantom relative to the linear accelerator. Results: Statistical errors from US-to-US registrations for various patient orientations ranged from 0.1 to 1.7 mm for x, y, and z translation components, and 0.0-1.1° for rotational components. Statistical errors from US-to-CT registrations were 0.3-1.2 mm for the x, y and z translational components and 0.1-2.5° for the rotational components. Conclusions: An ultrasound-based platform was designed, constructed and tested on a CT/US tissue-equivalent phantom to track bladder displacement with a statistical uncertainty to correct and track inter- and intra-fractional displacements of the bladder during radiation treatments

The association between family and community social capital and health risk behaviours in young people: an integrative review

Background: Health risk behaviours known to result in poorer outcomes in adulthood are generally established in late childhood and adolescence. These ‘risky’ behaviours include smoking, alcohol and illicit drug use and sexual risk taking. While the role of social capital in the establishment of health risk behaviours in young people has been explored, to date, no attempt has been made to consolidate the evidence in the form of a review. Thus, this integrative review was undertaken to identify and synthesise research findings on the role and impact of family and community social capital on health risk behaviours in young people and provide a consolidated evidence base to inform multi-sectorial policy and practice.<p></p> Methods: Key electronic databases were searched (i.e. ASSIA, CINAHL, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Embase, Medline, PsycINFO, Sociological Abstracts) for relevant studies and this was complemented by hand searching. Inclusion/exclusion criteria were applied and data was extracted from the included studies. Heterogeneity in study design and the outcomes assessed precluded meta-analysis/meta-synthesis; the results are therefore presented in narrative form.<p></p> Results: Thirty-four papers satisfied the review inclusion criteria; most were cross-sectional surveys. The majority of the studies were conducted in North America (n=25), with three being conducted in the UK. Sample sizes ranged from 61 to 98,340. The synthesised evidence demonstrates that social capital is an important construct for understanding the establishment of health risk behaviours in young people. The different elements of family and community social capital varied in terms of their saliency within each behavioural domain, with positive parent–child relations, parental monitoring, religiosity and school quality being particularly important in reducing risk.<p></p> Conclusions: This review is the first to systematically synthesise research findings about the association between social capital and health risk behaviours in young people. While providing evidence that may inform the development of interventions framed around social capital, the review also highlights key areas where further research is required to provide a fuller account of the nature and role of social capital in influencing the uptake of health risk behaviours.<p></p&gt