13 research outputs found
ColMix -- A Simple Data Augmentation Framework to Improve Object Detector Performance and Robustness in Aerial Images
In the last decade, Convolutional Neural Network (CNN) and transformer based
object detectors have achieved high performance on a large variety of datasets.
Though the majority of detection literature has developed this capability on
datasets such as MS COCO, these detectors have still proven effective for
remote sensing applications. Challenges in this particular domain, such as
small numbers of annotated objects and low object density, hinder overall
performance. In this work, we present a novel augmentation method, called
collage pasting, for increasing the object density without a need for
segmentation masks, thereby improving the detector performance. We demonstrate
that collage pasting improves precision and recall beyond related methods, such
as mosaic augmentation, and enables greater control of object density. However,
we find that collage pasting is vulnerable to certain out-of-distribution
shifts, such as image corruptions. To address this, we introduce two simple
approaches for combining collage pasting with PixMix augmentation method, and
refer to our combined techniques as ColMix. Through extensive experiments, we
show that employing ColMix results in detectors with superior performance on
aerial imagery datasets and robust to various corruptions
Promoting Sustainable Development of Cultural Assets by Improving Users' Perception through Space Configuration; Case Study: The Industrial Heritage Site
The role of the cultural assets as one of the pillars of sustainable development is undeniably of great significance in the cultural sustainability of cities. Indeed, the way users understand and interpret cultural heritage sites would be highly critical to managing cultural organizations properly. It means by improving users’ perception of these sites, it can expect a fair distribution of comprehensive awareness among generations about the values of cultural assets. Past studies in spatial psychology have demonstrated that environmental properties can positively Influence human emotions. On the other hand, using computational–mathematical methods used to examine spatio-visual properties have rarely been compared to human perceptions. This paper examines the impact of spatio-visual properties on human perception as a clever cultural management strategy to promote cultural sustainability. It is discussed how environmental features in general, and visibility in particular, can shape the way users interpret cultural heritage. Results indicate that not only visibility of users’ paths within cultural heritage sites can be an influential factor for the development of users’ perception, but also the visibility of the entrance of these complexes can change their understanding. This means that decision-makers, architects, and managers of the cultural organizations can apply these findings as cultural management framework by defining predefined paths in these sites in the way that they possess high visibility and visible entrance. Consequently, the distribution of public awareness among generations can be improved to strengthen the role of cultural aspects in sustainable development
Phase II Final Report Computer Optimization of Electron Guns
This program implemented advanced computer optimization into an adaptive mesh, finite element, 3D, charged particle code. The routines can optimize electron gun performance to achieve a specified current, beam size, and perveance. It can also minimize beam ripple and electric field gradients. The magnetics optimization capability allows design of coil geometries and magnetic material configurations to achieve a specified axial magnetic field profile. The optimization control program, built into the charged particle code Beam Optics Analyzer (BOA) utilizes a 3D solid modeling package to modify geometry using design tables. Parameters within the graphical user interface (currents, voltages, etc.) can be directly modified within BOA. The program implemented advanced post processing capability for the optimization routines as well as the user. A Graphical User Interface allows the user to set up goal functions, select variables, establish ranges of variation, and define performance criteria. The optimization capability allowed development of a doubly convergent multiple beam gun that could not be designed using previous techniques
Evaluating the Attribute of Industrial Heritage in Urban Context on Natural Movement Distribution. The Case Study of Dezful City
Space configuration of industrial heritage sites, which have been adaptively reused, are modeled in the depth map. Simultaneously, by using in-situ observation the actual patterns of pedestrian movement in these sites are captured. Finally, the results of simulated patterns and actual patterns are compared and interpreted. Findings show a notable impact of built heritage on the natural movement's patterns. Consequently, the significance of determinative factors of natural movement in these sites differs from regular sites. Therefore, this exception could develop a tourism policy towards these sites. By acknowledging the fact that the functions of selected case studies are not the same, yet those are the only adaptive reuse practice of industrial heritage in that region. This paper aims to assess the possible impact of built heritage as an influential attraction on distribution patterns of natural movement and develop natural movement theory in these sites. The use of natural movement theory, which provides accurate data that proves the impact of industrial heritage scientifically, is the main indicator of this research. this theory has not been used as an exact tool to identify the behavioral-movement attributes of heritage and needs some consideration to be applied in cultural heritage sites
Anti-disialosyl-immunoglobulin M chronic autoimmune neuropathies: a nationwide multicenter retrospective study.
In this retrospective study involving 14 university hospitals from France and Switzerland, the aim was to define the clinicopathological features of chronic neuropathies with anti-disialosyl ganglioside immunoglobulin M (IgM) antibodies (CNDA).
Fifty-five patients with a polyneuropathy evolving for more than 2 months and with at least one anti-disialosyl ganglioside IgM antibody, that is, anti-GD1b, -GT1b, -GQ1b, -GT1a, -GD2 and -GD3, were identified. Seventy-eight percent of patients were male, mean age at disease onset was 55 years (30-76) and disease onset was progressive (82%) or acute (18%). Patients presented with limb sensory symptoms (94% of cases), sensory ataxia (85%), oculomotor weakness (36%), limb motor symptoms (31%) and bulbar muscle weakness (18%). Sixty-five percent of patients had a demyelinating polyradiculoneuropathy electrodiagnostic profile and 24% a sensory neuronopathy profile. Anti-GD1b antibodies were found in 78% of cases, whilst other anti-disialosyl antibodies were each observed in less than 51% of patients. Other features included nerve biopsy demyelination (100% of cases), increased cerebrospinal fluid protein content (75%), IgM paraprotein (50%) and malignant hemopathy (8%). Eighty-six percent of CNDA patients were intravenous immunoglobulins-responsive, and rituximab was successfully used as second-line treatment in 50% of cases. Fifteen percent of patients had mild symptoms and were not treated. CNDA course was progressive (55%) or relapsing (45%), and 93% of patients still walked after a mean disease duration of 11 years.
Chronic neuropathies with anti-disialosyl ganglioside IgM antibodies have a recognizable phenotype, are mostly intravenous immunoglobulins-responsive and present with a good outcome in a majority of cases