scholarly journals Structures of Central Bulges and Nuclei of Galaxies

1974 ◽  
Vol 58 ◽  
pp. 335-340 ◽  
Author(s):  
G. De Vaucouleurs
Keyword(s):  
High Resolution ◽  
Central Peak ◽  
Small Object ◽  
Small Nucleus

The isophotal surfaces of central bulges of normal spirals, often described as ‘spheroidal’, are shown to depart from ellipsoids of revolution and to resemble MacLaurin or Jacobi spheroids with zonal distortion; two typical examples, NGC 4565, 5746, are illustrated. Weaker examples are NGC 2683, 4594 and 891. Stronger examples are NGC 7332 and 128.The true nucleus of an ordinary spiral is at most a very small object (~ 10 pc) resolved only in the nearest galaxies. The apparently larger nuclei seen in more distant spirals and lenticulars, in particular the so-called N-types, are probably artifacts due to insufficient resolution. It is possible that even in M31 the small ‘nucleus’ is merely the seeing-convolved image of the central peak in the r1/4 luminosity distribution of the spheroidal component.In the nearest barred lenticulars and early spirals each large ellipsoidal ‘nucleus’ (~ 1.0 × 1.5 kpc) in the centre of the bar or central lens is found to include a second bar and inner nucleus on a smaller scale, in the approximate ratio of the corresponding Jeans' lengths. This is illustrated by high resolution photographs of NGC 1291; another example is NGC 1326.

scholarly journals Pest Animal's Detection, and Habitat Identification in Low-resolution Airborne Thermal Imagery

2020 ◽  
Author(s):  
Anwaar Ulhaq
Keyword(s):  
Invasive Species ◽  
High Resolution ◽  
Object Detection ◽  
Visual Analysis ◽  
Detection System ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Small Object ◽  
Pest Species ◽  
Thermal Imagery

Invasive species are significant threats to global agriculture and food security being the major causes of crop loss. An operative biosecurity policy requires full automation of detection and habitat identification of the potential pests and pathogens. Unmanned Aerial Vehicles (UAVs) mounted thermal imaging cameras can observe and detect pest animals and their habitats, and estimate their population size around the clock. However, their effectiveness becomes limited due to manual detection of cryptic species in hours of captured flight videos, failure in habitat disclosure and the requirement of expensive high-resolution cameras. Therefore, the cost and efficiency trade-off often restricts the use of these systems. In this paper, we present an invasive animal species detection system that uses cost-effectiveness of consumer-level cameras while harnessing the power of transfer learning and an optimised small object detection algorithm. Our proposed optimised object detection algorithm named Optimised YOLO (OYOLO) enhances YOLO (You Only Look Once) by improving its training and structure for remote detection of elusive targets. Our system, trained on the massive data collected from New South Wales and Western Australia, can detect invasive species (rabbits, Kangaroos and pigs) in real-time with a higher probability of detection (85–100 %), compared to the manual detection. This work will enhance the visual analysis of pest species while performing well on low, medium and high-resolution thermal imagery, and equally accessible to all stakeholders and end-users in Australia via a public cloud.

scholarly journals Single Object Tracking in Satellite Videos: Deep Siamese Network Incorporating an Interframe Difference Centroid Inertia Motion Model

2021 ◽  
Vol 13 (7) ◽  
pp. 1298
Author(s):  
Kun Zhu ◽  
Xiaodong Zhang ◽  
Guanzhou Chen ◽  
Xiaoliang Tan ◽  
Puyun Liao ◽  
...  
Keyword(s):  
High Resolution ◽  
Object Tracking ◽  
Space Station ◽  
Small Object ◽  
Single Object ◽  
Siamese Network ◽  
Tracking Tasks ◽  
Sensing Platforms ◽  
Comparison Results ◽  
Multiple Moving Targets

Satellite video single object tracking has attracted wide attention. The development of remote sensing platforms for earth observation technologies makes it increasingly convenient to acquire high-resolution satellite videos, which greatly accelerates ground target tracking. However, overlarge images with small object size, high similarity among multiple moving targets, and poor distinguishability between the objects and the background make this task most challenging. To solve these problems, a deep Siamese network (DSN) incorporating an interframe difference centroid inertia motion (ID-CIM) model is proposed in this paper. In object tracking tasks, the DSN inherently includes a template branch and a search branch; it extracts the features from these two branches and employs a Siamese region proposal network to obtain the position of the target in the search branch. The ID-CIM mechanism was proposed to alleviate model drift. These two modules build the ID-DSN framework and mutually reinforce the final tracking results. In addition, we also adopted existing object detection datasets for remotely sensed images to generate training datasets suitable for satellite video single object tracking. Ablation experiments were performed on six high-resolution satellite videos acquired from the International Space Station and “Jilin-1” satellites. We compared the proposed ID-DSN results with other 11 state-of-the-art trackers, including different networks and backbones. The comparison results show that our ID-DSN obtained a precision criterion of 0.927 and a success criterion of 0.694 with a frames per second (FPS) value of 32.117 implemented on a single NVIDIA GTX1070Ti GPU.

Fraunhofer in-line electron holography of frozen-hydrated DNA superhelices

1994 ◽  
Vol 52 ◽  
pp. 128-129
Author(s):  
Takao Matsumoto ◽  
Takayoshi Tanji ◽  
Akira Tonomura
Keyword(s):  
Electron Beam ◽  
High Resolution ◽  
Phase Shift ◽  
Heavy Atom ◽  
Specimen Preparation ◽  
Electron Holography ◽  
Small Object ◽  
Biological Specimen ◽  
Supercoiled Dna ◽  
Gold Particles

We have visualized DNA molecules in solution by Fraunhofer in-line electron holography. So far, applications of the technique at high resolution have been limited to gold particles. This report is the first application of Fraunhofer in-line electron holography to a nanometer-sized biological specimen.The phase shift of an electron beam due to DNA is so small, estimated as only 2π/33 for 100-keV electrons, that it has been only possible to visualize them with either heavy-atom staining or metal shadowing techniques. However, these methods give only low-resolution images of the molecules, and worst of all, preservation of specimens is poor. The frozen-hydrated specimen preparation improved the preservation of specimen, and images of naturally supercoiled DNA in solution have been visualized using underfocusing of 1-2 μm. Such a defocusing is large enough for such a small object as DNA (diameter ∽ 2 nm) to be in a Fresnel condition; z ≈ a2/λ, where z is the defocusing, a is the diameter of an object, and λ is the wavelength.

scholarly journals Lidar transmitter offers “non-diffracting” property through short distance in highly-dense random media

2018 ◽  
Vol 176 ◽  
pp. 08019
Author(s):  
Xiafukaiti Alifu ◽  
Peng Ziqi ◽  
Tatsuo Shiina
Keyword(s):  
High Resolution ◽  
Laboratory Experiment ◽  
Milk Fat ◽  
Short Distance ◽  
Random Media ◽  
Propagation Distance ◽  
Central Peak ◽  
Forward Scattering ◽  
Narrow View

Non-diffracting beam (NDB) is useful in lidar transmitter because of its high propagation efficiency and high resolution. We aimed to generate NDB in random media such as haze and cloud. The laboratory experiment was conducted with diluted processed milk (fat: 1.8%, 1.1μmφ). Narrow view angle detector of 5.5mrad was used to detect the forward scattering waveform. We obtained the central peak of NDB at the propagation distance of 5cm ~ 30cm in random media by adjusting the concentration of <10%.

scholarly journals Multi-pinhole collimator design for small-object imaging with SiliSPECT: a high-resolution SPECT

2008 ◽  
Vol 54 (2) ◽  
pp. 207-225 ◽  
Author(s):  
S Shokouhi ◽  
S D Metzler ◽  
D W Wilson ◽  
T E Peterson
Keyword(s):  
High Resolution ◽  
Small Object ◽  
Pinhole Collimator ◽  
Object Imaging

scholarly journals Instance Segmentation for Governmental Inspection of Small Touristic Infrastructure in Beach Zones Using Multispectral High-Resolution WorldView-3 Imagery

2021 ◽  
Vol 10 (12) ◽  
pp. 813
Author(s):  
Osmar Luiz Ferreira de Carvalho ◽  
Rebeca dos Santos de Moura ◽  
Anesmar Olino de Albuquerque ◽  
Pablo Pozzobon de Bem ◽  
Rubens de Castro Pereira ◽  
...  
Keyword(s):  
High Resolution ◽  
Object Detection ◽  
Sliding Window ◽  
Coastal Areas ◽  
Image Resolution ◽  
Small Object ◽  
Original Image ◽  
Individual Object ◽  
High Resolution Images ◽  
Instance Segmentation

Misappropriation of public lands is an ongoing government concern. In Brazil, the beach zone is public property, but many private establishments use it for economic purposes, requiring constant inspection. Among the undue targets, the individual mapping of straw beach umbrellas (SBUs) attached to the sand is a great challenge due to their small size, high presence, and agglutinated appearance. This study aims to automatically detect and count SBUs on public beaches using high-resolution images and instance segmentation, obtaining pixel-wise semantic information and individual object detection. This study is the first instance segmentation application on coastal areas and the first using WorldView-3 (WV-3) images. We used the Mask-RCNN with some modifications: (a) multispectral input for the WorldView3 imagery (eight channels), (b) improved the sliding window algorithm for large image classification, and (c) comparison of different image resizing ratios to improve small object detection since the SBUs are small objects (<322 pixels) even using high-resolution images (31 cm). The accuracy analysis used standard COCO metrics considering the original image and three scale ratios (2×, 4×, and 8× resolution increase). The average precision (AP) results increased proportionally to the image resolution: 30.49% (original image), 48.24% (2×), 53.45% (4×), and 58.11% (8×). The 8× model presented 94% AP50, classifying nearly all SBUs correctly. Moreover, the improved sliding window approach enables the classification of large areas providing automatic counting and estimating the size of the objects, proving to be effective for inspecting large coastal areas and providing insightful information for public managers. This remote sensing application impacts the inspection cost, tribute, and environmental conditions.

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