Localization Uncertainty Estimation for Anchor-Free Object Detection

Since many safety-critical systems, such as surgical robots and autonomous driving cars, are in unstable environments with sensor noise and incomplete data, it is desirable for object detectors to take into account the confidence of localization prediction. There are three limitations of the prior uncertainty estimation methods for anchor-based object detection. 1) They model the uncertainty based on object properties having different characteristics, such as location (center point) and scale (width, height). 2) they model a box offset and ground-truth as Gaussian distribution and Dirac delta distribution, which leads to the model misspecification problem. Because the Dirac delta distribution is not exactly represented as Gaussian, i.e., for any $\mu$ and $\Sigma$. 3) Since anchor-based methods are sensitive to hyper-parameters of anchor, the localization uncertainty modeling is also sensitive to these parameters. Therefore, we propose a new localization uncertainty estimation method called Gaussian-FCOS for anchor-free object detection. Our method captures the uncertainty based on four directions of box offsets~(left, right, top, bottom) that have similar properties, which enables to capture which direction is uncertain and provide a quantitative value in range~[0, 1]. To this end, we design a new uncertainty loss, negative power log-likelihood loss, to measure uncertainty by weighting IoU to the likelihood loss, which alleviates the model misspecification problem. Experiments on COCO datasets demonstrate that our Gaussian-FCOS reduces false positives and finds more missing-objects by mitigating over-confidence scores with the estimated uncertainty. We hope Gaussian-FCOS serves as a crucial component for the reliability-required task

Edge-carboxylated graphene nanoplatelets as oxygen-rich metal-free cathodes for organic dye-sensitized solar cells

Edge-carboxylated graphene nanoplatelets (ECGnPs) were synthesized by the simple, efficient and eco-friendly ball-milling of graphite in the presence of dry ice and used as oxygen-rich metal-free counter electrodes (CEs) in organic dye-sensitized solar cells (DSSCs), for the first time. The resultant ECGnPs are soluble in many polar solvents including 2-propanol due to the polar nature of numerous carboxylic acids at edges, allowing an electrostatic spray (e-spray) to be deposited on fluorine-doped SnO2 (FTO)/glass substrates. The ECGnP-CE exhibited profound improvements in the electrochemical stability for the Co(bpy)3 2+/3+ redox couple compared to the platinum (Pt)-CE. The charge transfer resistance (RCT), related to the interface between an electrolyte and a CE, was significantly reduced to 0.87 ?? cm2, much lower than those of (Pt)-CE (2.19 ?? cm 2), PEDOT:PSS-CE (2.63 ?? cm2) and reduced graphene oxide (rGO)-CE (1.21 ?? cm2). The DSSC based on the JK-303-sensitizer and ECGnP-CE displayed a higher photovoltaic performance (FF, Jsc, and ??, 74.4%, 14.07 mA cm-2 and 9.31%) than those with the Pt-CE (71.6%, 13.69 mA cm-2 and 8.67%), PEDOT:PSS (68.7%, 13.68 mA cm-2 and 8.25%) and rGO-CE (72.9%, 13.88 mA cm-2 and 8.94%).close3

사용자경험의 개념과 범위 고찰을 위한 문헌연구

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성공적인 블록체인 서비스를 위한 제안: 서비스 가치와 기능 및 문제점 분석

2

Usability Evaluation for Cryptocurrency Exchange

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Building a Database of 4D Movie Clips Eliciting Affect/Emotions

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Stochastic fluctuation and transport of tokamak edge plasmas with the resonant magnetic perturbation field

We present that a statistical method known as the complexity-entropy analysis is useful to characterize a state of plasma turbulence and flux in the resonant magnetic perturbation (RMP) edge localized mode (ELM) control experiment. The stochastic pedestal top temperature fluctuation in the RMP ELM suppression phase is distinguished from the chaotic fluctuation in the natural ELM-free phase. It is discussed that the stochastic temperature fluctuation can be originated from the narrow layer of the field penetration on the pedestal top. The forced magnetic island can emit the resonant drift wave of comparable sizes (relatively low-k) in the RMP ELM suppression phase, and it can result in the generation of stochastic higher wavenumber fluctuations coupled to tangled fields around the island. The analysis of the ion saturation current measurement around the major outer striking point on the divertor shows that it also becomes more stochastic as the stronger plasma response to the RMP field is expected. © 2022 Author(s).11Nsciescopu

Stochastic fluctuation and transport of tokamak edge plasmas with the resonant magnetic perturbation field

We present that a statistical method known as the complexity???entropy analysis is useful to characterize a state of plasma turbulence and flux in the resonant magnetic perturbation (RMP) edge localized mode (ELM) control experiment. The stochastic pedestal top temperature fluctuation in the RMP ELM suppression phase is distinguished from the chaotic fluctuation in the natural ELM-free phase. It is discussed that the stochastic temperature fluctuation can be originated from the narrow layer of the field penetration on the pedestal top. The forced magnetic island can emit the resonant drift wave of comparable sizes (relatively low-k) in the RMP ELM suppression phase, and it can result in the generation of stochastic higher wavenumber fluctuations coupled to tangled fields around the island. The analysis of the ion saturation current measurement around the major outer striking point on the divertor shows that it also becomes more stochastic as the stronger plasma response to the RMP field is expected. I. INTRODUCTIO