Depth-embedded instance segmentation network for urban scene parsing

2021 ◽  
pp. 1-11
Author(s):  
Zhifan Wang ◽  
Tong Xin ◽  
Shidong Wang ◽  
Haofeng Zhang
Keyword(s):  
Large Scale ◽  
Cost Effective ◽  
Autonomous Driving ◽  
Depth Information ◽  
Stereo Images ◽  
Exploration And Exploitation ◽  
Urban Scene ◽  
Different Depths ◽  
Effective Use ◽  
Instance Segmentation

 The ubiquitous availability of cost-effective cameras has rendered large scale collection of street view data a straightforward endeavour. Yet, the effective use of these data to assist autonomous driving remains a challenge, especially lack of exploration and exploitation of stereo images with abundant perceptible depth. In this paper, we propose a novel Depth-embedded Instance Segmentation Network (DISNet) which can effectively improve the performance of instance segmentation by incorporating the depth information of stereo images. The proposed network takes binocular images as input to observe the displacement of the object and estimate the corresponding depth perception without additional supervisions. Furthermore, we introduce a new module for computing the depth cost-volume, which can be integrated with the colour cost-volume to jointly capture useful disparities of stereo images. The shared-weights structure of Siamese Network is applied to learn the intrinsic information of stereo images while reducing the computational burden. Extensive experiments have been carried out on publicly available datasets (i.e., Cityscapes and KITTI), and the obtained results clearly demonstrate the superiority in segmenting instances with different depths.

scholarly journals Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images

2021 ◽  
Vol 13 (16) ◽  
pp. 3065
Author(s):  
Libo Wang ◽  
Rui Li ◽  
Dongzhi Wang ◽  
Chenxi Duan ◽  
Teng Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
Texture Features ◽  
Semantic Segmentation ◽  
Autonomous Driving ◽  
Research Field ◽  
Learning Approaches ◽  
Fine Grained ◽  
Urban Scene ◽  
Fine Resolution ◽  
With Memory

Semantic segmentation from very fine resolution (VFR) urban scene images plays a significant role in several application scenarios including autonomous driving, land cover classification, urban planning, etc. However, the tremendous details contained in the VFR image, especially the considerable variations in scale and appearance of objects, severely limit the potential of the existing deep learning approaches. Addressing such issues represents a promising research field in the remote sensing community, which paves the way for scene-level landscape pattern analysis and decision making. In this paper, we propose a Bilateral Awareness Network which contains a dependency path and a texture path to fully capture the long-range relationships and fine-grained details in VFR images. Specifically, the dependency path is conducted based on the ResT, a novel Transformer backbone with memory-efficient multi-head self-attention, while the texture path is built on the stacked convolution operation. In addition, using the linear attention mechanism, a feature aggregation module is designed to effectively fuse the dependency features and texture features. Extensive experiments conducted on the three large-scale urban scene image segmentation datasets, i.e., ISPRS Vaihingen dataset, ISPRS Potsdam dataset, and UAVid dataset, demonstrate the effectiveness of our BANet. Specifically, a 64.6% mIoU is achieved on the UAVid dataset.

scholarly journals New frontiers in enzyme immobilisation: robust biocatalysts for a circular bio-based economy

2021 ◽  
Author(s):  
Roger A. Sheldon ◽  
Alessandra Basso ◽  
Dean Brady
Keyword(s):  
Cost Effective ◽  
Continuous Processing ◽  
Enzyme Immobilisation ◽  
Recent Advances ◽  
Effective Use

This tutorial review focuses on recent advances in technologies for enzyme immobilisation, enabling their cost-effective use in the bio-based economy and continuous processing in general.

Efficient Schedule of Energy-Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery

2021 ◽  
Vol 5 (1) ◽  
pp. 1-23
Author(s):  
Yan Pan ◽  
Shining Li ◽  
Qianwu Chen ◽  
Nan Zhang ◽  
Tao Cheng ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Load Capacity ◽  
Scheduling Algorithm ◽  
Cost Effective ◽  
Promising Alternative ◽  
Logistics Industry ◽  
Last Mile ◽  
Delivery Scheduling ◽  
Schedule Approach

Stimulated by the dramatical service demand in the logistics industry, logistics trucks employed in last-mile parcel delivery bring critical public concerns, such as heavy cost burden, traffic congestion and air pollution. Unmanned Aerial Vehicles (UAVs) are a promising alternative tool in last-mile delivery, which is however limited by insufficient flight range and load capacity. This paper presents an innovative energy-limited logistics UAV schedule approach using crowdsourced buses. Specifically, when one UAV delivers a parcel, it first lands on a crowdsourced social bus to parcel destination, gets recharged by the wireless recharger deployed on the bus, and then flies from the bus to the parcel destination. This novel approach not only increases the delivery range and load capacity of battery-limited UAVs, but is also much more cost-effective and environment-friendly than traditional methods. New challenges therefore emerge as the buses with spatiotemporal mobility become the bottleneck during delivery. By landing on buses, an Energy-Neutral Flight Principle and a delivery scheduling algorithm are proposed for the UAVs. Using the Energy-Neutral Flight Principle, each UAV can plan a flying path without depleting energy given buses with uncertain velocities. Besides, the delivery scheduling algorithm optimizes the delivery time and number of delivered parcels given warehouse location, logistics UAVs, parcel locations and buses. Comprehensive evaluations using a large-scale bus dataset demonstrate the superiority of the innovative logistics UAV schedule approach.

scholarly journals Multi-Country Scale Assessment of Available Energy Recovery Potential Using Micro-Hydropower in Drinking, Pressurised Irrigation and Wastewater Networks, Covering Part of the EU

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 899
Author(s):  
Djordje Mitrovic ◽  
Miguel Crespo Chacón ◽  
Aida Mérida García ◽  
Jorge García Morillo ◽  
Juan Antonio Rodríguez Diaz ◽  
...  
Keyword(s):  
Drinking Water ◽  
Northern Ireland ◽  
Energy Recovery ◽  
Large Scale ◽  
Significant Proportion ◽  
Value Added ◽  
Cost Effective ◽  
Net Energy ◽  
Water Networks ◽  
Scale Assessment

Studies have shown micro-hydropower (MHP) opportunities for energy recovery and CO2 reductions in the water sector. This paper conducts a large-scale assessment of this potential using a dataset amassed across six EU countries (Ireland, Northern Ireland, Scotland, Wales, Spain, and Portugal) for the drinking water, irrigation, and wastewater sectors. Extrapolating the collected data, the total annual MHP potential was estimated between 482.3 and 821.6 GWh, depending on the assumptions, divided among Ireland (15.5–32.2 GWh), Scotland (17.8–139.7 GWh), Northern Ireland (5.9–8.2 GWh), Wales (10.2–8.1 GWh), Spain (375.3–539.9 GWh), and Portugal (57.6–93.5 GWh) and distributed across the drinking water (43–67%), irrigation (51–30%), and wastewater (6–3%) sectors. The findings demonstrated reductions in energy consumption in water networks between 1.7 and 13.0%. Forty-five percent of the energy estimated from the analysed sites was associated with just 3% of their number, having a power output capacity >15 kW. This demonstrated that a significant proportion of energy could be exploited at a small number of sites, with a valuable contribution to net energy efficiency gains and CO2 emission reductions. This also demonstrates cost-effective, value-added, multi-country benefits to policy makers, establishing the case to incentivise MHP in water networks to help achieve the desired CO2 emissions reductions targets.

scholarly journals Modeling Fused Filament Fabrication using Artificial Neural Networks

2021 ◽  
Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Cost Effective ◽  
Print Quality ◽  
Ann Model ◽  
Production Environment ◽  
Fused Filament Fabrication ◽  
Artificial Neural ◽  
Using Data ◽  
Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

The socio-spatial politics of royalties and their distribution: A case study of the Surat Basin, Queensland

2021 ◽  
pp. 0308518X2110266
Author(s):  
Neil Argent ◽  
Sean Markey ◽  
Greg Halseth ◽  
Laura Ryser ◽  
Fiona Haslam-McKenzie
Keyword(s):  
Cost Effective ◽  
Indigenous Communities ◽  
Energy Extraction ◽  
Grant Application ◽  
Coal Seam Gas ◽  
Spatial Politics ◽  
Developmental Needs ◽  
Development Fund ◽  
Effective Use

This paper is concerned with the socio-spatial and ethical politics of redistribution, specifically the allocation of natural resources rents from political and economic cores to the economic and geographical peripheries whence the resource originated. Based on a case study of the coal seam gas sector in Queensland's Surat Basin, this paper focuses on the operation of the Queensland State Government's regional development fund for mining and energy extraction-affected regions. Employing an environmental justice framework, we critically explore the operation of these funds in ostensibly helping constituent communities in becoming resilient to the worst effects of the ‘staples trap’. Drawing on secondary demographic and housing data for the region, as well as primary information collected from key respondents from mid-2018 to early 2019, we show that funds were distributed across all of the local government areas, and allocated to projects and places primarily on a perceived economic needs basis. However, concerns were raised with the probity of the funds’ administration. In terms of recognition justice, the participation of smaller and more remote towns and local Indigenous communities was hampered by their structural marginalisation. Procedurally, the funds were criticised for the lack of local consultation taken in the development and approval of projects. While spatially concentrated expenditure may be the most cost-effective use of public monies, we argue that grant application processes should be open, transparent and inclusive, and the outcomes cognisant of the developmental needs of smaller communities, together with the need to foster regional solidarity and coherence.

scholarly journals Anti-meningococcal B vaccination in Italian adolescents: a cost-effective health opportunity

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
D Panatto ◽  
P Landa ◽  
D Amicizia ◽  
P L Lai ◽  
E Lecini ◽  
...  
Keyword(s):  
Large Scale ◽  
Public Health Problem ◽  
Vaccination Strategy ◽  
Cost Effective ◽  
Dose Schedule ◽  
Developed Countries ◽  
Invasive Disease ◽  
International Setting ◽  
The Impact

Abstract Background Invasive disease due to Neisseria meningitidis (Nm) is a serious public health problem even in developed countries, owing to its high lethality rate (8-15%) and the invalidating sequelae suffered by many (up to 60%) survivors. As the microorganism is transmitted via the airborne route, the only available weapon in the fight against Nm invasive disease is vaccination. Our aim was to carry out an HTA to evaluate the costs and benefits of anti-meningococcal B (MenB) vaccination with Trumenba® in adolescents in Italy, while also considering the impact of this new vaccination strategy on organizational and ethics aspects. Methods A lifetime Markov model was developed. MenB vaccination with the two-dose schedule of Trumenba® in adolescents was compared with 'non-vaccination'. Two perspectives were considered: the National Health Service (NHS) and society. Three disease phases were defined: acute, post-acute and long-term. Epidemiological, economic and health utilities data were taken from Italian and international literature. The analysis was conducted by means of Microsoft Excel 2010®. Results Our study indicated that vaccinating adolescents (11th year of life) with Trumenba® was cost-effective with an ICER = € 7,912/QALY from the NHS perspective and € 7,758/QALY from the perspective of society. Vaccinating adolescents reduces the number of cases of disease due to meningococcus B in one of the periods of highest incidence of the disease, resulting in significant economic and health savings. Conclusions This is the first study to evaluate the overall impact of free MenB vaccination in adolescents both in Italy and in the international setting. Although cases of invasive disease due to meningococcus B are few, if the overall impact of the disease is adequately considered, it becomes clear that including anti-meningococcal B vaccination into the immunization program for adolescents is strongly recommended from the health and economic standpoints. Key messages Free, large-scale MenB vaccination is key to strengthening the global fight against invasive meningococcal disease. Anti-meningococcal B vaccination in adolescents is a cost-effective health opportunity.

scholarly journals Environmental Engineering Techniques to Restore Degraded Posidonia oceanica Meadows

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 661
Author(s):  
Luigi Piazzi ◽  
Stefano Acunto ◽  
Francesca Frau ◽  
Fabrizio Atzori ◽  
Maria Francesca Cinti ◽  
...  
Keyword(s):  
Large Scale ◽  
Natural Habitat ◽  
Cost Benefit ◽  
Cost Effective ◽  
Posidonia Oceanica ◽  
Environmental Engineering ◽  
Bottom Surface ◽  
Sessile Invertebrates ◽  
Set Up ◽  
Short Time

Seagrass planting techniques have shown to be an effective tool for restoring degraded meadows and ecosystem function. In the Mediterranean Sea, most restoration efforts have been addressed to the endemic seagrass Posidonia oceanica, but cost-benefit analyses have shown unpromising results. This study aimed at evaluating the effectiveness of environmental engineering techniques generally employed in terrestrial systems to restore the P. oceanica meadows: two different restoration efforts were considered, either exploring non-degradable mats or, for the first time, degradable mats. Both of them provided encouraging results, as the loss of transplanting plots was null or very low and the survival of cuttings stabilized to about 50%. Data collected are to be considered positive as the survived cuttings are enough to allow the future spread of the patches. The utilized techniques provided a cost-effective restoration tool likely affordable for large-scale projects, as the methods allowed to set up a wide bottom surface to restore in a relatively short time without any particular expensive device. Moreover, the mats, comparing with other anchoring methods, enhanced the colonization of other organisms such as macroalgae and sessile invertebrates, contributing to generate a natural habitat.

scholarly journals A Review on Terahertz Technologies Accelerated by Silicon Photonics

Nanomaterials ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1646
Author(s):  
Jingya Xie ◽  
Wangcheng Ye ◽  
Linjie Zhou ◽  
Xuguang Guo ◽  
Xiaofei Zang ◽  
...  
Keyword(s):  
Integrated Circuit ◽  
Silicon Photonics ◽  
Large Scale ◽  
Cost Effective ◽  
Single Chip ◽  
Photonic Integrated Circuit ◽  
Hybrid Silicon ◽  
The Cost ◽  
Silicon Based ◽  
Thz Applications

In the last couple of decades, terahertz (THz) technologies, which lie in the frequency gap between the infrared and microwaves, have been greatly enhanced and investigated due to possible opportunities in a plethora of THz applications, such as imaging, security, and wireless communications. Photonics has led the way to the generation, modulation, and detection of THz waves such as the photomixing technique. In tandem with these investigations, researchers have been exploring ways to use silicon photonics technologies for THz applications to leverage the cost-effective large-scale fabrication and integration opportunities that it would enable. Although silicon photonics has enabled the implementation of a large number of optical components for practical use, for THz integrated systems, we still face several challenges associated with high-quality hybrid silicon lasers, conversion efficiency, device integration, and fabrication. This paper provides an overview of recent progress in THz technologies based on silicon photonics or hybrid silicon photonics, including THz generation, detection, phase modulation, intensity modulation, and passive components. As silicon-based electronic and photonic circuits are further approaching THz frequencies, one single chip with electronics, photonics, and THz functions seems inevitable, resulting in the ultimate dream of a THz electronic–photonic integrated circuit.

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