Dynamic Body VSLAM with Semantic Constraints

Image based reconstruction of urban environments is a challenging problem that deals with optimization of large number of variables, and has several sources of errors like the presence of dynamic objects. Since most large scale approaches make the assumption of observing static scenes, dynamic objects are relegated to the noise modeling section of such systems. This is an approach of convenience since the RANSAC based framework used to compute most multiview geometric quantities for static scenes naturally confine dynamic objects to the class of outlier measurements. However, reconstructing dynamic objects along with the static environment helps us get a complete picture of an urban environment. Such understanding can then be used for important robotic tasks like path planning for autonomous navigation, obstacle tracking and avoidance, and other areas. In this paper, we propose a system for robust SLAM that works in both static and dynamic environments. To overcome the challenge of dynamic objects in the scene, we propose a new model to incorporate semantic constraints into the reconstruction algorithm. While some of these constraints are based on multi-layered dense CRFs trained over appearance as well as motion cues, other proposed constraints can be expressed as additional terms in the bundle adjustment optimization process that does iterative refinement of 3D structure and camera / object motion trajectories. We show results on the challenging KITTI urban dataset for accuracy of motion segmentation and reconstruction of the trajectory and shape of moving objects relative to ground truth. We are able to show average relative error reduction by a significant amount for moving object trajectory reconstruction relative to state-of-the-art methods like VISO 2, as well as standard bundle adjustment algorithms

Interpretation and localization of Thorax diseases using DCNN in Chest X-Ray

In recent years, the use of diagnosing images has been increased dramatically. An entry level task of diagnosing and reading Chest X-ray for radiologist but they ought to re-quire a good knowledge and careful observation of anatomical principles, pathology and physiology for this complex reasonings. In many modern hospital’s the tremendous number of x-ray images are stored in PACS (Picture Archiving and Communication Sys-tem). The conditions of plethora been diagnosed by the sustainable number of chest X-Ray. Our aim to predict the thorax disease categories through deep learning using chest x-rays and their first-pass specialist accuracy. In a paper the main application that present a pathology localization framework and multi-label unified weakly supervised image classification that can perceive the occurrence of afterward generation of bound-ing box around the consistent and multiple pathologies. Due to considering of large image capacity we adapt Deep Convolutional Neural Network (DCNN) architecture for weakly-supervised object localization, different pooling strategies, various multi-label CNN losses and measured against a baseline of softmax regression

Language Grounded QFormer for Efficient Vision Language Understanding

Large-scale pretraining and instruction tuning have been successful for training general-purpose language models with broad competencies. However, extending to general-purpose vision-language models is challenging due to the distributional diversity in visual inputs. A recent line of work explores vision-language instruction tuning, taking inspiration from the Query Transformer (QFormer) approach proposed in BLIP-2 models for bridging frozen modalities. However, these approaches rely heavily on large-scale multi-modal pretraining for representation learning before eventual finetuning, incurring a huge computational overhead, poor scaling, and limited accessibility. To that end, we propose a more efficient method for QFormer-based vision-language alignment and demonstrate the effectiveness of our strategy compared to existing baselines in improving the efficiency of vision-language pretraining.Comment: Preprint Under Revie

The influence of the terminal acceptor and oligomer length on the photovoltaic properties of A–D–A small molecule donors

Four new A–D–A small molecules (denoted as FG1–4) have been designed and synthesized. The compounds have cyclopentadithiophene-vinylene (CPDTV) oligomers of different lengths as the central donor core linked with different terminal acceptor units (3-ethylrhodanine or dicyanomethylene-3-ethylrhodanine). The effects that conjugation length and terminal acceptor units have on the optical and electrochemical properties were investigated. These small molecules were used as donors in conjunction with PC71BM as an acceptor in the bulk heterojunction active layer for the fabrication of solution-processed organic solar cells. Solvent vapor annealing treatment improved the crystallinity and the interpenetrating networks of donor and acceptor phases for exciton dissociation and charge transfer, thus leading to significant improvements in the overall power conversion efficiency (PCE) of the organic solar cells. The PCE values for the organic solar cells based on the optimized FG1:PC71BM, FG2:PC71BM, FG3:PC71BM and FG4:PC71BM active layer were 5.58%, 6.99%, 7.51% and 8.43%, respectively. These results indicate that an enhancement in the PCE of small molecule organic solar cells can be achieved by an increase in conjugation-length and variation of terminal acceptor units in the molecular backbone of small molecules and optimization of the crystallinity and nanoscale interpenetrating morphology by appropriate solvent vapor annealing treatment

Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019

Background Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. Methods We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (USMR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. Findings Global U5MR decreased from 71.2 deaths per 1000 livebirths (95% uncertainty interval WI] 68.3-74-0) in 2000 to 37.1 (33.2-41.7) in 2019 while global NMR correspondingly declined more slowly from 28.0 deaths per 1000 live births (26.8-29-5) in 2000 to 17.9 (16.3-19-8) in 2019. In 2019,136 (67%) of 204 countries had a USMR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030,154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9.65 million (95% UI 9.05-10.30) in 2000 and 5.05 million (4.27-6.02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3.76 million 95% UI 3.53-4.021) in 2000 to 48% (2.42 million; 2.06-2.86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0.80 (95% UI 0.71-0.86) deaths per 1000 livebirths and U5MR to 1.44 (95% UI 1-27-1.58) deaths per 1000 livebirths, and in 2019, there were as many as 1.87 million (95% UI 1-35-2.58; 37% 95% UI 32-43]) of 5.05 million more deaths of children younger than 5 years than the survival potential frontier. Interpretation Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve USMR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

Multimodal tracking for robust pose estimation

An on-line 3D visual object tracking framework for monocular cameras by incorporating spatial knowledge and uncertainty from semantic mapping along with high frequency measurements from visual odometry is presented. Using a combination of vision and odometry that are tightly integrated we can increase the overall performance of object based tracking for semantic mapping. We present a framework for integration of the two data-sources into a coherent framework through uncertainty based fusion/arbitration.M.S

Identifying public preferences using multi-criteria decision making for assessing the shift of urban commuters from private to public transport: A case study of Delhi

Shifting urban commuters to public transport can be an effective strategy to deal with the energy and environmental problems associated with the transport sector. In order to enhance public transport the mode of choice for urban commuters, public expectations and requirements should be at the centre of the policy-making process. This study uses pair-wise weighing method (i.e. Analytical Hierarchy Process) to derive priorities for different criteria for shifting urban commuters to the public transport system based on their opinion. The primary survey has been conducted to collect the data for identifying public preferences for public transport characteristics under four parent criteria: reliability, comfort, safety and cost, identified based on literature review and expert opinion. This information was collected using questionnaire based surveys between January 2013 and July 2013 from nearly 50 locations using a stratified random sampling technique from nine districts of Delhi. Our results suggest safety as the most important criteria (36% of total) for encouraging the urban commuters to shift from private vehicles to public transport and then reliability (27%), cost (21%) and comfort (16%). Based on above four criteria, commuters were found to be happy with Delhi metro services compared to buses and other mode of public transport due to more frequency, adherence to schedule, less travel time, comfort and safety. Commuters were willing to pay more for better public transport service since the travel cost was not considered to be one of the important criteria. The results also showed that 96% commuters are willing to shift to public transport if above criteria or services are considered for providing an efficient public transport system. These results can assist transport planners to integrate public preferences with the available technical alternatives for the wise allocation of the available resources