Application of convolutional neural networks and image processing algorithms based on traffic video in vehicle taillight detection

2021 ◽  
Vol 35 (3) ◽  
pp. 181
Author(s):  
Gangshan Wu ◽  
Taihe Lin ◽  
Wei Huo ◽  
Ning Cao
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Convolutional Neural Networks ◽  
Traffic Video ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Image-processing algorithms realized by discrete-time cellular neural networks and their circuit implementations

2006 ◽  
Vol 29 (5) ◽  
pp. 1100-1108 ◽  
Author(s):  
Hsin-Chieh Chen ◽  
Yung-Ching Hung ◽  
Chang-Kuo Chen ◽  
Teh-Lu Liao ◽  
Chun-Kuo Chen
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Discrete Time ◽  
Cellular Neural Networks ◽  
Image Processing Algorithms ◽  
Processing Algorithms

scholarly journals Convolutional neural network in the images colorization problem

2019 ◽  
pp. 340-353
Author(s):  
M V Bulygin ◽  
M M Gayanova ◽  
A M Vulfin ◽  
A D Kirillova ◽  
R Ch Gayanov
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Processing ◽  
Processing System ◽  
Black And White ◽  
Convolutional Networks ◽  
Advantages And Disadvantages ◽  
The Neural Network ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Object of the research are modern structures and architectures of neural networks for image processing. Goal of the work is improving the existing image processing algorithms based on the extraction and compression of features using neural networks using the colorization of black and white images as an example. The subject of the work is the algorithms of neural network image processing using heterogeneous convolutional networks in the colorization problem. The analysis of image processing algorithms with the help of neural networks is carried out, the structure of the neural network processing system for image colorization is developed, colorization algorithms are developed and implemented. To analyze the proposed algorithms, a computational experiment was conducted and conclusions were drawn about the advantages and disadvantages of each of the algorithms.

Otoconia perfect/imperfect crystals

1994 ◽  
Vol 52 ◽  
pp. 42-43
Author(s):  
César D. Fermin ◽  
Dale Martin
Keyword(s):  
Image Processing ◽  
Room Temperature ◽  
Phosphotungstic Acid ◽  
Gallus Domesticus ◽  
Crystal Matrix ◽  
Organic Templates ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Diffraction Patterns

Otoconia of higher vertebrates are interesting biological crystals that display the diffraction patterns of perfect crystals (e.g., calcite for birds and mammal) when intact, but fail to produce a regular crystallographic pattern when fixed. Image processing of the fixed crystal matrix, which resembles the organic templates of teeth and bone, failed to clarify a paradox of biomineralization described by Mann. Recently, we suggested that inner ear otoconia crystals contain growth plates that run in different directions, and that the arrangement of the plates may contribute to the turning angles seen at the hexagonal faces of the crystals.Using image processing algorithms described earlier, and Fourier Transform function (2FFT) of BioScan Optimas®, we evaluated the patterns in the packing of the otoconia fibrils of newly hatched chicks (Gallus domesticus) inner ears. Animals were fixed in situ by perfusion of 1% phosphotungstic acid (PTA) at room temperature through the left ventricle, after intraperitoneal Nembutal (35mg/Kg) deep anesthesia. Negatives were made with a Hitachi H-7100 TEM at 50K-400K magnifications. The negatives were then placed on a light box, where images were filtered and transferred to a 35 mm camera as described.

Elastic Graph-based Semi-supervised Embedding with Adaptive Loss Regression

2020 ◽  
Keyword(s):  
Image Processing ◽  
International Symposium ◽  
Fast Track ◽  
Electronic Imaging ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Fast track article for IS&T International Symposium on Electronic Imaging 2020: Image Processing: Algorithms and Systems proceedings.

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