86 research outputs found

    Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation

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    Pixel-level annotations are expensive and time-consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recent years have seen great progress in weakly-supervised semantic segmentation, whether from a single image or from videos. However, most existing methods are designed to handle a single background class. In practical applications, such as autonomous navigation, it is often crucial to reason about multiple background classes. In this paper, we introduce an approach to doing so by making use of classifier heatmaps. We then develop a two-stream deep architecture that jointly leverages appearance and motion, and design a loss based on our heatmaps to train it. Our experiments demonstrate the benefits of our classifier heatmaps and of our two-stream architecture on challenging urban scene datasets and on the YouTube-Objects benchmark, where we obtain state-of-the-art results.Comment: 11 pages, 4 figures, 7 tables, Accepted in ICCV 201

    Development of a non-iterative macromodeling technique by data integration and least square method

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    In this paper, a new method is introduced to synthesize the original data obtained from simulation or measurement results in the form of a rational function. The integration of the available data is vital to the performance of the proposed method. The values of poles and residues of the rational model are determined by solving the system of linear equations using conventional Least Square Method (LSM). To ensure the stability condition of the provided model, a controller coefficient is considered. Also, using this parameter, the designer can increase the stability margin of a system with poor stability conditions. The introduced method has the potential to be used for a wide range of practical applications since there is no specific restriction on the use of this method. The only requirement that should be considered is Dirichlet condition for the original data, usually the case for physical systems. To verify the performances of the proposed method, several application test cases were investigated and the obtained results were compared with those gathered by the well-known vector fitting algorithm. Also, the examinations showed that the method is efficient in the presence of noisy data

    The Study of Abnormal Liver Ultrasound Findings in Candidate Patients Undergoing Renal Transplantation from Brain Dead Donors

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    BACKGROUND AND OBJECTIVE: Chronic kidney disease in addition to kidney involvement may cause abnormalities in various systems of the body, in which liver disorders are one of the most commonly encountered disorders. Failure to identify some of these disorders can cause a serious problem in transolant patient. This study was performed to determine the frequency and type of abnormal liver ultrasound findings in renal transplant patients. METHODS: In this cross-sectional study, recorded data of 480 kidney failure patients who had received kidney transplant from brain death donors during the last 6 years in three Mashhad hospitals were investigated. Ultrasonography was considered before the transplant and abnormal liver findings were recorded in a checklist and were assesed. FINDINGS: The mean age was 39.07±12.67 years of which 52.70% were male and 42.30% were female. Liver disorders were observed in 13.12% of patients. The highest prevalence was related to fatty liver grade I (2.5%), grade II (1.46%), gallstone (1.25%) and liver cysts (1.25%). CONCLUSION: The results of the study showed that liver asymptomatic disorders in renal transplant patients have significant prevalence and because some of these disorders require treatment before transplantation, enough attention to screening before transplantation can help to prevent post-transplant complications

    A new approach for the recovery of polyphenols from Arthrospira platensis: advancement of green process through high pressure/temperature extraction

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    The cyanobacterium Arthrospira (Spirulina) platensis was used as raw material for the recovery of polyphenols by the high temperature/high pressure extraction process, to be used as ingrediet for fuctional foods preparation

    Influence of Temperature and Drying Time on Extraction Yield of Phenolic Compounds from Grape Pomace Variety “Portogizac”

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    The influence of drying temperature (60 °C, 70 °C, 80 °C) and fluid-bed drying time (90 min, 135 min, 180 min) on the extraction yield of phenolic compounds and antioxidant activity of extracts were investigated. The content of phenolic compounds and antioxidant activity of extracts obtained from wet grape pomace (WGP) were 73.83 mgGAE gdb–1, 42.24 mgCE gdb–1, 30.53 mg gdb–1, and 0.35 ginhDPPH gdb–1 for total phenolic compounds (TPC), total flavonoids (TF), total extractible proanthocyanidins (TPA), and antioxidant activity (AA), respectively. The applied drying conditions caused the reduction of content of all phenolic compounds down to 13.2 %, 43.1 %, 15.3 % and 21.0 % for TPC, TPA, TF and AA, respectively. The most abundant individual phenolic compound in grape pomace extracts was catechin (5.14 – 8.52 mg gdb–1). The highest content of observed compounds was retained when applying drying temperature below 70 °C for 90 minutes

    Recovery of phenolic compounds from Arthrospira (Spirulina) platensis: an approach on green extraction through innovative alternative techniques for food application

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    New innovating extraction technology for the recovery of phenolic compounds from biomass of the cyanobacterium Arthrospira (Spirulina) platensis have been used. The extracts have been evaluated as ingredient to fortify functional foods

    An Efficient Multi-Beam Array Architecture for L-Band Secondary Surveillance Radars

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    In this paper, the design and fabrication of a large array antenna with three required, Sum, Difference and Control beams for a monopulse Secondary Surveillance Radar (SSR) is presented. A special array element, which is a high gain dual dipole structure, is designed and tested. This element has 9.6 dB gain in 1060 MHz and does not need any balun. The main challenge of extracting three beams out of one beam feeding networks (BFN) has been resolved efficiently by maximum integration of all three in one network, reducing the number of required modules to one half. The complete 33-element array, working in 1030 MHz and 1090 MHz is designed based on the Taylor array factor. The complex feed network of this 6-meter long array has successfully been synthesized as modular as possible. Sum pattern was designed for 2.7o azimuth beam width and -20 dB side lobe level and Diff pattern with a deep null in the boresight of the Sum pattern. The Ctrl beam was also designed in order to cover the Sum beam except in the direction of the main lobe
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