Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders

Convolutional autoencoders have emerged as popular methods for unsupervised defect segmentation on image data. Most commonly, this task is performed by thresholding a pixel-wise reconstruction error based on an $\ell^p$ distance. This procedure, however, leads to large residuals whenever the reconstruction encompasses slight localization inaccuracies around edges. It also fails to reveal defective regions that have been visually altered when intensity values stay roughly consistent. We show that these problems prevent these approaches from being applied to complex real-world scenarios and that it cannot be easily avoided by employing more elaborate architectures such as variational or feature matching autoencoders. We propose to use a perceptual loss function based on structural similarity which examines inter-dependencies between local image regions, taking into account luminance, contrast and structural information, instead of simply comparing single pixel values. It achieves significant performance gains on a challenging real-world dataset of nanofibrous materials and a novel dataset of two woven fabrics over the state of the art approaches for unsupervised defect segmentation that use pixel-wise reconstruction error metrics

Paul, The Pastor (His Corinthian Ministry)

Here, in this city of lewdness and immorality, of gross dishonesty and crying sins, the Apostle Paul preached the message of Christ Crucified. He rarely stayed in any city as long as he did in Corinth. Christ was the Savior even of publicans and sinners, hence even this stronghold of iniquity and vice was to be conquered with the Gospel of Christ

Optimal or antagonistic? muscle force solutions in the lower limb

Provides evidence of the appropriateness of different muscle force distribution protocols in a musculoskeletal model of the lower limb

Revisiting and revitalizing political ecology in the American West

Political ecology, initially conceived to better understand the power relations implicit in management and distribution of natural resources in the developing world, came “home” to the American West in the 1990s and 2000s. This groundswell of research did much to problematize socio-environmental conflicts in the region, long typified by tensions over land and resources, identity and belonging, autonomy and authority. Since first touching down in the West, however, the “big tent” of political ecology has only grown bigger, incorporating new perspectives, epistemologies, and ontologies. At the same time, the nexus of environment and society is perhaps even more salient today, amid a regional conjuncture of populist revolt, climate change, and rapid political economic transformation. Here we reflect on three longstanding regional concerns – energy development, wolf reintroduction, and participatory governance – leveraging the pluralism of contemporary political ecology to better understand their contemporary incarnations. In so doing, we highlight the need to bring together insights from both “traditional” approaches and newer directions to better understand and engage contemporary challenges, with their heightened stakes and complexity. Such an approach demonstrates what we might learn about global processes in this place, as well as what insights regional praxis (often woefully provincial) might gain from elsewhere – new ways of seeing and doing political ecology. Our goal is to generate discussion among and between political ecologists and regional critical scholars, initiating new collaborative engagements that might serve the next wave of political ecology in the 21st century American West

Motives and Incentives for Data Sharing in Industrial Data Ecosystems: An Explorative Single Case Study

The increasing connectivity of the business world leads to economic value being created less and less by one company alone, but rather through the exchange and combination of data by various actors in so-called data ecosystems. However, many companies are not yet willing to participate in data ecosystems because they do not see the added value of their participation. This is partly because the motives of data providers do not match the incentives offered to share their data. So far, there are only very few studies that deal with this issue in detail. Therefore, we close this research gap by adopting a conceptual model to the issue of motives and incentives for data sharing and applying it to the industrial data ecosystem Catena-X in a single case study. Through the case study analysis, we can identify seven different motives and eight incentives for data sharing

Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings

We introduce a powerful student-teacher framework for the challenging problem of unsupervised anomaly detection and pixel-precise anomaly segmentation in high-resolution images. Student networks are trained to regress the output of a descriptive teacher network that was pretrained on a large dataset of patches from natural images. This circumvents the need for prior data annotation. Anomalies are detected when the outputs of the student networks differ from that of the teacher network. This happens when they fail to generalize outside the manifold of anomaly-free training data. The intrinsic uncertainty in the student networks is used as an additional scoring function that indicates anomalies. We compare our method to a large number of existing deep learning based methods for unsupervised anomaly detection. Our experiments demonstrate improvements over state-of-the-art methods on a number of real-world datasets, including the recently introduced MVTec Anomaly Detection dataset that was specifically designed to benchmark anomaly segmentation algorithms.Comment: Accepted to CVPR 202

Modulation of Asymmetric Division Diversity through Cytokinin and SPEECHLESS Regulatory Interactions in the Arabidopsis Stomatal Lineage

Coordinated growth of organs requires communication among cells within and between tissues. In plants, leaf growth is largely dictated by the epidermis; here, asymmetric and self-renewing divisions of the stomatal lineage create two essential cell types—pavement cells and guard cells—in proportions reflecting inputs from local, systemic, and environmental cues. The transcription factor SPEECHLESS (SPCH) is the prime regulator of divisions, but whether and how it is influenced by external cues to provide flexible development is enigmatic. Here, we show that the phytohormone cytokinin (CK) can act as an endogenous signal to affect the extent and types of stomatal lineage divisions and forms a regulatory circuit with SPCH. Local domains of low CK signaling are created by SPCH-dependent cell-type-specific activity of two repressive type-A ARABIDOPSIS RESPONSE REGULATORs (ARRs), ARR16 and ARR17, and two secreted peptides, CLE9 and CLE10, which, together with SPCH, can customize epidermal cell-type composition

Absolute quantitation of coronary steal induced by intravenous dipyridamole

AbstractOBJECTIVESThe study was done to determine whether coronary steal (defined as an absolute decrease in perfusion from resting blood flow) is induced by intravenous (IV) dipyridamole in patients with severe coronary artery disease (CAD).BACKGROUNDMyocardial ischemia during coronary vasodilation is usually attributed to coronary steal. However, there is limited data on the absolute magnitude of coronary steal in humans.METHODSEighteen patients with multivessel CAD underwent dynamic positron emission tomography (PET) imaging with 13NH3at rest and after infusion of IV dipyridamole. Eight myocardial sectors were analyzed per short axis slice and myocardial blood flow calculated with a two-compartment model in absolute terms.RESULTSCoronary steal occurred in 8 of the 18 patients. In the 8 patients with coronary steal, myocardial blood flow decreased from 90 ± 18 ml/100 g/min at rest to 68 ± 27 ml/100 g/min following dipyridamole in the segments with steal, and increased from 87 ± 19 to 138 ± 16 ml/100 g/min following dipyridamole in the segments without steal. Significant clinical correlates of coronary steal were either ST elevation or the combination of ST depression and angina.CONCLUSIONSCoronary vasodilation with IV dipyridamole is associated with significant reductions in blood flow to collateral-dependent myocardium consistent with coronary steal in about 45% of patients with severe CAD