Towards Accurate One-Stage Object Detection with AP-Loss

One-stage object detectors are trained by optimizing classification-loss and localization-loss simultaneously, with the former suffering much from extreme foreground-background class imbalance issue due to the large number of anchors. This paper alleviates this issue by proposing a novel framework to replace the classification task in one-stage detectors with a ranking task, and adopting the Average-Precision loss (AP-loss) for the ranking problem. Due to its non-differentiability and non-convexity, the AP-loss cannot be optimized directly. For this purpose, we develop a novel optimization algorithm, which seamlessly combines the error-driven update scheme in perceptron learning and backpropagation algorithm in deep networks. We verify good convergence property of the proposed algorithm theoretically and empirically. Experimental results demonstrate notable performance improvement in state-of-the-art one-stage detectors based on AP-loss over different kinds of classification-losses on various benchmarks, without changing the network architectures. Code is available at https://github.com/cccorn/AP-loss.Comment: 13 pages, 7 figures, 4 tables, main paper + supplementary material, accepted to CVPR 201

Facile Synthesis of Nitrogen-doped Porous Carbon for Selective CO2 Capture

AbstractSolid-state post-combustion CO2 sorbents have certain advantages over traditional aqueous amine systems, including reduced regeneration energy since vaporization of liquid water is avoided, tunable pore morphology, and greater chemical variability. We report here an ordered mesoporous nitrogen-doped carbon made by the co- assembly of a modified-pyrrole and triblock copolymer through a soft-templating method, which is facile, economic, and fast compared to the hard-template approach. A high surface area mesoporous carbon was achieved, which is comparable to the silica counterpart. This porous carbon, with a Brunauer–Emmett–Teller (BET) specific surface area of 804.5 m2 g-1, exhibits large CO2 capacities (298K) of 1.0 and 3.1 mmol g-1 at 0.1 and 1bar, respectively, and excellent CO2/N2 selectivity of 51.4. The porous carbon can be fully regenerated solely by inert gas purging without heating. It is stable for multiple adsorption/desorption cycles without reduction in CO2 capacity. These desirable properties render the nitrogen-doped hierarchical porous carbon a promising material for post-combustion CO2 capture

Design and testing of sorbents for CO2 separation of post-combustion and natural gas sweetening applications

In post-combustion processes, sorbents with both high capacity and selectivity are required for reducing the cost of carbon capture. Although physisorbents have the advantage of low energy consumption for regeneration, it remains a challenge to obtain both high capacity and sufficient CO2/N2 selectivity at the same time. A novel N-doped hierarchical carbon has been developed, which exhibits record-high Henry’s law CO2/N2 selectivity among physisorptive carbons while having a high CO2 adsorption capacity. Specifically, the synthesis involves the rational design of a modified pyrrole molecule that can co-assemble with the soft Pluronic template via hydrogen bonding and electrostatic interactions to give rise to mesopores followed by carbonization. The low-temperature carbonization and activation processes allow for the development of ultra-small pores (d2 affinity. Furthermore, the described work provides a strategy to initiate the development of rationally-designed porous conjugated polymer structures and carbon-based materials for various potential applications. In addition to post-combustion capture, natural gas sweetening is another topic of interest. Natural gas, having the lowest carbon intensity compared to coal and petroleum, is projected to increase in production and consumption in the coming decades. However, a drawback associated with natural gas is that it contains considerable amounts of CO2 at the recovery well, making on-site CO2 capture necessary. Solid sorbents are advantageous over traditional amine scrubbing due to their relatively low regeneration energies and non-corrosive nature. However, it remains a challenge to improve the sorbent’s CO2 capacity at elevated pressures relevant to natural gas purification. A series of porous carbons have been developed, which were derived from an intrinsic 3D hierarchical nanostructured polymer hydrogel, with simple and effective tunability over the pore size distribution. The optimized surface area reached a record-high of 4196 m2 g-1 among carbon-based materials. This high surface area along with the abundant micro/narrow mesopores (1.94 cm3 g-1 with d \u3c 4 nm) results in a record-high CO2 capacity (28.3 mmol g-1 at 25 °C and 30 bar) among carbons. This carbon also showed reasonable CO2/CH4 selectivity and excellent cyclability. In addition, this work for the first time combines experimental studies with first-principle molecular simulations for high-pressure CO2 adsorption on porous sorbents. It was found that at elevated pressures, the CO2 density in the adsorbed phase is significantly enhanced in the micro- and narrow mesopores with quantitative values provided for CO2 density. Furthermore, surface nitrogen functionalities have a trivial contribution to the CO2 uptake at high pressures. These findings emphasize the importance of being able to tune a sorbent’s pore size to achieve high CO2 uptake. Thus, the simulation studies help in our understanding of our sorbent’s superior performance as well as provides useful insight into future sorbent development