1,720,975 research outputs found

    Analisi archeometriche dei materiali lapidei delle terme

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    Sono stati caratterizzati dal punto di vista minero-petrografico, paleontologico, chimico e geochimico venti campioni di materiali lapidei dall'area termale (II- III AD) del sito archeologico di Herdonia (Foggia, Italy

    Quando lo sgrassante è di troppo. Un'indagine critica sui dati archeometrici

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    This work investigates, through archaeological classification and archaeometric analysis, the ceramic production from the Middle Neolithic occupation at the site of Yumuktepe, on the Mediterranean coast of Turkey. The levels that have been investigated and are reported in this work correspond to a period from 6200 to 5800 BC, as dated by radiocarbon samples. It is an early period in pottery production, even though technical capacities already show a quite specialised production

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Augmented Grad-CAM: Heat-Maps Super Resolution Through Augmentation

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    We present Augmented Grad-CAM, a general framework to provide a high-resolution visual explanation of CNN outputs. Our idea is to take advantage of image augmentation to aggregate multiple low-resolution heat-maps - in our experiments Grad-CAMs - computed from augmented copies of the same input image. We generate the high-resolution heat-map through super-resolution, and we formulate a general optimization problem based on Total Variation regularization. This problem is entirely solved on the GPU at inference time, together with image augmentation. Augmented Grad-CAM outperforms Grad-CAM in weakly supervised localization on Imagenet dataset, and provides more detailed heat-maps. Moreover, Augmented Grad-CAM turns to be particularly useful in monitoring the production of silicon wafers, where CNNs are employed to classify defective patterns on the wafer surface to detect harmful faults in the production line
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