Optimization of Rooftop Delineation from Aerial Imagery with Deep Learning

High-definition (HD) maps of building rooftops or footprints are important for urban application and disaster management. Rapid creation of such HD maps through rooftop delineation at the city scale using high-resolution satellite and aerial images with deep leaning methods has become feasible and draw much attention. In the context of rooftop delineation, the end-to-end Deep Convolutional Neural Networks (DCNNs) have demonstrated remarkable performance in accurately delineating rooftops from aerial imagery. However, several challenges still exist in this task, which are addressed in this thesis. These challenges include: (1) the generalization issues of models when test data differ from training data, (2) the scale-variance issues in rooftop delineation, and (3) the high cost of annotating accurate rooftop boundaries. To address the challenges mentioned above, this thesis proposes three novel deep learning-based methods. Firstly, a super-resolution network named Momentum and Spatial-Channel Attention Residual Feature Aggregation Network (MSCA-RFANet) is proposed to tackle the generalization issue. The proposed super-resolution network shows better performance compared to its baseline and other state-of-the-art methods. In addition, data composition with MSCA-RFANet shows high performance on dealing with the generalization issues. Secondly, an end-to-end rooftop delineation network named Higher Resolution Network with Dynamic Scale Training (HigherNet-DST) is developed to mitigate the scale-variance issue. The experimental results on publicly available building datasets demonstrate that HigherNet-DST achieves competitive performance in rooftop delineation, particularly excelling in accurately delineating small buildings. Lastly, a weakly supervised deep learning network named Box2Boundary is developed to reduce the annotation cost. The experimental results show that Box2Boundary with post processing is effective in dealing with the cost annotation issues with decent performance. Consequently, the research with these three sub-topics and the three resulting papers are thought to hold potential implications for various practical applications

Local Binary Fitting Segmentation by Cooperative Quantum Particle Optimization

Recently, sophisticated segmentation techniques, such as level set method, which using valid numerical calculation methods to process the evolution of the curve by solving linear or nonlinear elliptic equations to divide the image availably, has become being more popular and effective. In Local Binary Fitting (LBF) algorithm, a simple contour is initialized in an image and then the steepest-descent algorithm is employed to constrain it to minimize the fitting energy functional. Hence, the initial position of the contour is difficult or impossible to be well chosen for the final performance. To overcoming this drawback, this work treats the energy fitting problem as a meta-heuristic optimization algorithm and imports a varietal particle swarm optimization (PSO) method into the inner optimization process. The experimental results of segmentations on medical images show that the proposed method is not only effective to both simple and complex medical images with adequate stochastic effects, but also shows the accuracy and high efficiency

On-line Partial Discharge Localization of 10-kV Covered Conductor Lines

This paper proposes an innovative partial discharge (PD) location technique for overhead electrical power distribution networks. It is aimed at improving the condition-based maintenance of the network. PD localization is carried out via an improved double-sided traveling-wave method. The method is driven by a hybrid detection technique, which integrates a pulse-based synchronization mechanism and a global positioning system (GPS). The proposed solution offers a number of benefits. It has the nice inherent feature of being immune to varying physical parameters of the transmission line, and it has been proven be offer improved accuracy with respect of the conventional GPS-based location methods. Also, an in-house designed portable and non-invasive test setup is presented and thoroughly discussed, thus demonstrating the feasibility of the proposed method. Moreover, an enhanced algorithm is embedded into the PD location system to improve robustness to high-level noise. Finally, the proposed tool relies on a well-established automatic procedure which requires neither parameter tuning nor any expert intervention. The features and strengths of the method are validated on a real case consisting of a 2125-m long 10-kV overhead covered conductor line

NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review

Neural Radiance Field (NeRF), a new novel view synthesis with implicit scene representation has taken the field of Computer Vision by storm. As a novel view synthesis and 3D reconstruction method, NeRF models find applications in robotics, urban mapping, autonomous navigation, virtual reality/augmented reality, and more. Since the original paper by Mildenhall et al., more than 250 preprints were published, with more than 100 eventually being accepted in tier one Computer Vision Conferences. Given NeRF popularity and the current interest in this research area, we believe it necessary to compile a comprehensive survey of NeRF papers from the past two years, which we organized into both architecture, and application based taxonomies. We also provide an introduction to the theory of NeRF based novel view synthesis, and a benchmark comparison of the performance and speed of key NeRF models. By creating this survey, we hope to introduce new researchers to NeRF, provide a helpful reference for influential works in this field, as well as motivate future research directions with our discussion section

Comparative Study of the Amount of Re-released Hemoglobin from α-Thalassemia and Hereditary Spherocytosis Erythrocytes

Hemoglobin release test (HRT), which is established by our lab, is a new experiment to observe the re-released hemoglobin (Hb) from erythrocytes. In this study, one-dimension HRT, double dimension HRT, and isotonic and hypotonic HRT were performed to observe the re-released Hb from the blood samples of normal adult, hereditary spherocytosis (HS), and α-thalassemia. The results showed that compared with normal adult, the re-released Hb from HS blood sample was decreased significantly; however, the re-released Hb from α-thalassemia blood sample was increased significantly. The mechanism of this phenomenon was speculated to have relation with the abnormal amount of membrane-binding Hb

Production of the top-pions at the THERA collider based γp\gamma p collisions

In the framework of the topcolor-assisted technicolor (TC2) models, we study the production of the top-pions $\pi^{0}_{t}$, $\pi_{t}^{\pm}$ via the processes $ep\to\gamma c\to\pi^{0}_{t}c$ and $ep\to\gamma c\to\pi^{\pm}_{t}b$ mediated by the anomalous top coupling $tc\gamma$. We find that the production cross section of the process $ep\to\gamma c\to\pi^{0}_{t}c$ is very small. With reasonable values of the parameters in TC2 models, the production cross section of the process $ep\to\gamma c\to\pi^{\pm}_{t}b$ can reach $1.2pb$. The charged top-pions $\pi^{\pm}_{t}$ might be directly observed via this process at the THERA collider based $\gamma p$ collisions.Comment: 10 pages, 3 figure

Association of MDR1 G2677T polymorphism and leukemia risk: evidence from a meta-analysis

In the light of the relationship between the MDR1 G2677T polymorphism and the risk of leukemia remains inclusive or controversial. For better understanding of the effect of MDR1 G2677T polymorphism on leukemia risk, we performed a meta-analysis. Eligible studies were identified through a search of electronic databases such as PubMed, Excerpta Medica Database (Embase), Cochrane Library, and Chinese Biomedical Literature Database (CBM). The association between the MDR1 G2677T polymorphism and leukemia risk was conducted by odds ratios (ORs) and 95 % confidence intervals (95 % CI). A total of seven publications including eight studies with 1,229 cases and 1,097 controls were included in the meta-analysis. There was no association between MDR1 G2677T polymorphism and leukemia risk in all of five models in overall populations (T vs. G: OR = 1.00, 95 % CI = 0.88–1.12, P = 0.914; TT vs. GG: OR = 0.97, 95 % CI = 0.75–1.26, P = 0.812; TG vs. GG: OR = 1.00, 95 % CI = 0.92–1.08, P = 0.939; TT vs. TG/GG: OR = 0.98, 95 % CI = 0.67–1.43, P = 0.906; TT/TG vs. GG: OR = 1.00, 95 % CI = 0.95–1.06, P = 0.994). However, the significant association was found in others (Table 2) under the homozygote model (TT vs. GG: OR = 0.68, 95 % CI = 0.48–0.94, P = 0.020) and recessive model (TT vs. TG/GG: OR = 0.63, 95 % CI = 0.43–0.92, P = 0.016). In the subgroup analysis, according to the type of leukemia, significant association was found between MDR1 G2677T polymorphism and myeloid leukemia but not lymphoblastic leukemia (TT vs. GG: OR = 0.66, 95 % CI = 0.46–0.95, P = 0.026; TT vs. TG/GG: OR = 0.56, 95 % CI = 0.38–0.84, P = 0.005). The results suggested that there was no association between MDR1 G2677T polymorphism and leukemia risk in overall populations, but significant association was found in others populations (Asians and Africans), and myeloid leukemia indicated that G2677T polymorphism might be a protective factor in the susceptibility of myeloid leukemia and in Asians and Africans

Beyond the ceremony: Mega-event, air quality and political career

This paper examines whether mega-events-initiated planning regulations improved air quality in Chinese cities and explores the driving forces of the enforcement of such regulations. Using the 2008 Beijing Olympics as an example, we find that mega-events serve as an opportunity for cities to combat air pollution. The 2008 Olympics prompted a handful of Chinese cities to cut pollution and sustain a blue sky: Cities with air quality regulated for the Olympics cut their Air Pollution Index by about 16 points during the Games, compared to non-regulated cities, and 60% of that effect remained four years after the event. These achievements are obtained through effective mobilization of city leaders by associating air quality with their political careers. This study reveals that 1) a mega-event may improve urban environmental quality beyond the host cities and the event period, and 2) successful implementation of environmental regulations hinges on incentivizing local leaders