Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

Modern object detectors usually suffer from low accuracy issues, as foregrounds always drown in tons of backgrounds and become hard examples during training. Compared with those proposal-based ones, real-time detectors are in far more serious trouble since they renounce the use of region-proposing stage which is used to filter a majority of backgrounds for achieving real-time rates. Though foregrounds as hard examples are in urgent need of being mined from tons of backgrounds, a considerable number of state-of-the-art real-time detectors, like YOLO series, have yet to profit from existing hard example mining methods, as using these methods need detectors fit series of prerequisites. In this paper, we propose a general hard example mining method named Loss Rank Mining (LRM) to fill the gap. LRM is a general method for real-time detectors, as it utilizes the final feature map which exists in all real-time detectors to mine hard examples. By using LRM, some elements representing easy examples in final feature map are filtered and detectors are forced to concentrate on hard examples during training. Extensive experiments validate the effectiveness of our method. With our method, the improvements of YOLOv2 detector on auto-driving related dataset KITTI and more general dataset PASCAL VOC are over 5% and 2% mAP, respectively. In addition, LRM is the first hard example mining strategy which could fit YOLOv2 perfectly and make it better applied in series of real scenarios where both real-time rates and accurate detection are strongly demanded.Comment: 8 pages, 6 figure

Benchmark study of the two-dimensional Hubbard model with auxiliary-field quantum Monte Carlo method

Ground-state properties of the Hubbard model on a two-dimensional square lattice are studied by the auxiliary-field quantum Monte Carlo method. Accurate results for energy, double occupancy, effective hopping, magnetization, and momentum distribution are calculated for interaction strengths of U/t from 2 to 8, for a range of densities including half-filling and n = 0.3,0.5,0.6, 0.75, and 0.875. At half-filling, the results are numerically exact. Away from half-filling, the constrained path Monte Carlo method is employed to control the sign problem. Our results are obtained with several advances in the computational algorithm, which are described in detail. We discuss the advantages of generalized Hartree-Fock trial wave functions and its connection to pairing wave functions, as well as the interplay with different forms of Hubbard-Stratonovich decompositions. We study the use of different twist angle sets when applying the twist averaged boundary conditions. We propose the use of quasirandom sequences, which improves the convergence to the thermodynamic limit over pseudorandom and other sequences. With it and a careful finite size scaling analysis, we are able to obtain accurate values of ground-state properties in the thermodynamic limit. Detailed results for finite-sized systems up to 16 x 16 are also provided for benchmark purposes

Coupling quantum Monte Carlo and independent-particle calculations: Self-consistent constraint for the sign problem based on the density or the density matrix

Quantum Monte Carlo (QMC) methods are one of the most important tools for studying interacting quantum many-body systems. The vast majority of QMC calculations in interacting fermion systems require a constraint to control the sign problem. The constraint involves an input trial wave function which restricts the random walks. We introduce a systematically improvable constraint which relies on the fundamental role of the density or one-body density matrix. An independent-particle calculation is coupled to an auxiliary-field QMC calculation. The independent-particle solution is used as the constraint in QMC, which then produces the input density or density matrix for the next iteration. The constraint is optimized by the self-consistency between the many-body and the independent-particle calculations. The approach is demonstrated in the two-dimensional Hubbard model by accurately determining the ground state when collective modes separated by tiny energy scales are present in the magnetic and charge correlations. Our approach also provides an ab initio way to predict effective interaction parameters for independent-particle calculations

Evaluation of recanalisation treatment on posterior circulation ischemic stroke by Solitaire device—A multicenter retrospective study

Objectives Posterior circulation ischemic stroke (PCIS), accounting for approximately 20% of total ischemic stroke, is a sever disease that associated with high rate of morbidity and mortality. Though the effectiveness of endovascular mechanical thrombectomy has been well demonstrated in many types of ischemic stroke, it is still unclear what the outcome is in posterior circulation ischemic stroke. Methods and materials In current study, data was collected from 139 Chinese patients who received endovascular mechanical thrombectomy treatment with Solitaire device after acute posterior circulation ischemic stroke. We measured the mortality, symptomatic intracranial hemorrhage (SICH) and National Institutes of Health Stroke Scale (NIHSS) to evaluate the safety of endovascular mechanical thrombectomy. Meanwhile, the clinical outcome of endovascular mechanical thrombectomy was also evaluated based on recanalisation rate, HIHSS, and the modified Rankin Scale (mRS). Results Recanalisation was successful in 124 (89.3%) patients after surgery. Herniation was the second fatal stroke complication, out of the 6 patients suffered from herniation, 3 patients (50%) died during surgery and 2 (33%) died after surgery. As for other stroke complications such as pulmonary infection, 1 patient (4.3%) died during surgery and 1 patient (4.3%) died 3 days after surgery. Conclusion Our findings indicate that endovascular mechanical treatment is a safe treatment which brings clear benefit to patients suffered from posterior circulation ischemic stroke, in both the recanalisation rate and functional outcomes