An effective RGB color selection for complex 3D object structure in scene graph systems

Van, Chung Le; Nguyen, Gia Nhu; Nguyen, Tam T. T. N.; Nguyen, Trieu; Le, Dac‐Nhuong

doi:10.11591/ijece.v10i6.pp5951-5964

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…But for N>3 images, the visualization of the changes is not so immediate anymore. It is possible to go through animations, as in [9] which make it possible to differentiate the permanent type changes from those which are occasional changes, but these products remain video objects [10], which do not address the problem of temporal reduction, allowing the result of a single product summarizing all the changes that have occurred [11].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the visualizing changes in radar time series using the REACTIV method through satellite imagery

Hamid

Chisab

2022

IJECE

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<span>A visualizing temporal stack of synthetic aperture radar (SAR) images are presented in this work, the method is called REACTIV, which enabled us to highlight color zones that have undergone change over the detected period of time. This work has been widely tested using Google earth engine (GEE) platform, this method depends on the hue-saturation-value (HSV) of visualizing space and supports estimation only in the time domain; the method does not support the spatial estimation. The coefficient of temporal coefficient variation is coded depending on the saturation color, of which several statistical properties are described. The limitations are studied, and some applications are implemented in this study.</span>

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Section: Introductionmentioning

confidence: 99%

Analysis of the visualizing changes in radar time series using the REACTIV method through satellite imagery

Hamid

Chisab

2022

IJECE

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“…There are many HBC signal propagation models like the finite difference time domain (FDTD) method, analytical electromagnetic model, finite element method (FEM), and general circuit model that are selected for data transmission in the human body [4]. The HBC is designed for wearable computing, sensing, medical, and other portable wireless networking applications [5]. The WBAN is used in most medical applications like disease monitoring [6], handling medical emergencies using a Software-defined network [7], hearing aids [8], and realtime patient monitoring at high throughput [9].…”

Section: Introductionmentioning

confidence: 99%

Design and performance analysis of human body communication digital transceiver for wireless body area network applications

Lokanatha¹,

Prashanth²

2022

IJECE

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Wireless body area network (WBAN) is a prominent technology for resolving health-care concerns and providing high-speed continuous monitoring and real-time help. Human body communication (HBC) is an IEEE 802.15.6 physical layer standard for short-range communications that is not reliant on radio frequency (RF). Most WBAN applications can benefit from the HBC's low-latency and low-power architectural features. In this manuscript, an efficient digital HBC transceiver (TR) hardware architecture is designed as per IEEE 802.15.6 standard to overcome the drawbacks of the RF-wireless communication standards like signal leakage, on body antenna and power consumption. The design is created using a frequency selective digital transmission scheme for transmitter and receiver modules. The design resources are analyzed using different field programmable gate array (FPGA) families. The HBC TR utilizes <1% slices, consumes 101 mW power, and provides a throughput of 24.31 Mbps on Artix-7 FPGA with a latency of 10.5 clock cycles. In addition, the less than 10-4bit error rate of HBC is achieved with a 9.52 Mbps data rate. The proposed work is compared with existing architectures with significant improvement in performance parameters like chip area, power, and data rate.

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“…Deep learning approaches are mostly applied to the MRI and CT images due to its 360 degrees coverage of the human body part. An autonomous deep learning-based model was proposed to detect, identify and label the spine vertebrae in the MRI images [36][37][38], and the same in the case of CT images [39][40][41]. X-ray images and MRI/CT scan images have their own benefits and limitations.…”

Section: Introductionmentioning

confidence: 99%

Detecting Lumbar Implant and Diagnosing Scoliosis from Vietnamese X-Ray Imaging Using the Pre-Trained API Models and Transfer Learning

Van¹,

Bao²,

Puri³

et al. 2020

Computers, Materials &Amp; Continua

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With the rapid growth of the autonomous system, deep learning has become integral parts to enumerate applications especially in the case of healthcare systems. Human body vertebrae are the longest and complex parts of the human body. There are numerous kinds of conditions such as scoliosis, vertebra degeneration, and vertebrate disc spacing that are related to the human body vertebrae or spine or backbone. Early detection of these problems is very important otherwise patients will suffer from a disease for a lifetime. In this proposed system, we developed an autonomous system that detects lumbar implants and diagnoses scoliosis from the modified Vietnamese x-ray imaging. We applied two different approaches including pre-trained APIs and transfer learning with their pre-trained models due to the unavailability of sufficient x-ray medical imaging. The results show that transfer learning is suitable for the modified Vietnamese x-ray imaging data as compared to the pre-trained API models. Moreover, we also explored and analyzed four transfer learning models and two pre-trained API models with our datasets in terms of accuracy, sensitivity, and specificity.

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An effective RGB color selection for complex 3D object structure in scene graph systems

Cited by 4 publications

References 27 publications

Analysis of the visualizing changes in radar time series using the REACTIV method through satellite imagery

Analysis of the visualizing changes in radar time series using the REACTIV method through satellite imagery

Design and performance analysis of human body communication digital transceiver for wireless body area network applications

Detecting Lumbar Implant and Diagnosing Scoliosis from Vietnamese X-Ray Imaging Using the Pre-Trained API Models and Transfer Learning

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