Open set recognition through Monte Carlo dropout-based uncertainty

Open set recognition has received much attention in recent years. In this paper, we present a novel open set recognition method that is able to obtain improved recognition by applying Monte Carlo Dropout to capture uncertainty in order to yield high quality predicted probabilities. Experimental results on six benchmark datasets show that our method gives better open set recognition performance than other stateof-the-art methods, with at least 6.4%, 3.9%, 2.9% and 1.0% performance increase in AUROC on the challenging object datasets CIFAR-10, CIFAR+10, CIFAR+50 and TinyImageNet respectively. We also perform an analysis on the benefits of combining predictive uncertainty with an EVT-based open set recognition model which indicates that Monte Carlo Dropout-based uncertainty allows to obtain high quality predicted probabilities and to learn more accurate open set recognition scores. This, in turn, helps to reduce the overlap between known and unknown classes, thus making them more separable

Oxygen-Content-Controllable Graphene Oxide from Electron-Beam-Irradiated Graphite: Synthesis, Characterization, and Removal of Aqueous Lead [Pb(II)]

A high-energy electron beam was applied to irradiate graphite for the preparation of graphene oxide (GO) with a controllable oxygen content. The obtained GO sheets were analyzed with various characterization tools. The results revealed that the oxygen-containing groups of GO increased with increasing irradiation dosages. Hence, oxygen-content-controllable synthesis of GO can be realized by changing the irradiation dosages. The GO sheets with different irradiation dosages were then used to adsorb aqueous Pb­(II). The effects of contact time, pH, initial lead ion concentration, and ionic strength on Pb­(II) sorption onto different GO sheets were examined. The sorption process was found to be very fast (completed within 20 min) at pH 5.0. Except ionic strength, which showed no/little effect on lead sorption, the other factors affected the sorption of aqueous Pb­(II) onto GO. The maximum Pb­(II) sorption capacities of GO increased with irradiation dosages, confirming that electron-beam irradiation was an effective way to increase the oxygen content of GO. These results suggested that irradiated GO with a controllable oxygen content is a promising nanomaterial for environmental cleanup, particularly for the treatment of cationic metal ions, such as Pb­(II)