presently appearance of resistance to antifungal agents among aspergillus species is dramatically increasing. the objective of this study was to look at the in vitro activities of antifungal drugs against iranian clinical (from nail, bronchoalveolar lavage, paranasal sinus) isolated a. flavus strains. the susceptibility of 45 aflatoxigenic and non-aflatoxigenic aspergillus flavus strains were e...

Recently, alpha matting has received a lot of attention because its usefulness in mobile applications such as selfies. Therefore, there been demand for lightweight model due to the limited computational resources commercial portable devices. To this end, we suggest distillation-based channel pruning method networks. In step, remove channels student network having fewer impacts on mimicking know...

Extracting accurate foregrounds from natural images benefits many downstream applications such as film production and augmented reality. However, the furry characteristics various appearance of foregrounds, e.g., animal portrait, challenge existing matting methods, which usually require extra user inputs trimap or scribbles. To resolve these problems, we study distinct roles semantics details f...

We study the composition style in deep image matting, a notion that characterizes data generation flow on how to exploit limited foregrounds and random backgrounds form training dataset. Prior art executes this completely manner by simply going through foreground pool or optionally combining two before foreground-background composition. In work, we first show naive combination can be problemati...

To solve the problem that deep learning-based image matting algorithm cannot balance accuracy and model size, a lightweight based on learning is proposed. Considering limitation of memory computing resources, aiming at lightweight. We construct network gradually improved it. Firstly, apply detachable convolution to networks form faster stronger encoder decoder networks. The simultaneous use dep...