Torteeka, Peerapong

Preferred name

Torteeka, Peerapong

Now showing 1 - 10 of 20

Some of the metrics are blocked by your
consent settings
PCL-PTD Net: Parallel Cross-Learning-Based Pixel Transferred Deconvolutional Network for Building Extraction in Dense Building Areas With Shadow
(2023-01-01)
Boonpook, Wuttichai
;
Tan, Yumin
;
Torsri, Kritanai
;
Kamsing, Patcharin
;
Torteeka, Peerapong
Urban building segmentation from remote sensed imageries is challenging because there usually exists a variety of building features. Furthermore, very high spatial resolution imagery can provide many details of the urban building, such as styles, small gaps among buildings, building shadows, etc. Hence, satisfactory accuracy in detecting and extracting urban features from highly detailed images still remains. Deep learning semantic segmentation using baseline networks works well on building extraction; however, their ability in building extraction in shadows area, unclear building feature, and narrow gaps among buildings in dense building zone is still limited. In this article, we propose parallel cross-learning-based pixel transferred deconvolutional network (PCL-PTD net), and then is used to segment urban buildings from aerial photographs. The proposed method is evaluated and intercompared with traditional baseline networks. In PCL-PTD net, it is composed of parallel network, cross-learning functions, residual unit in encoder part, and PTD in decoder part. The performance is applied to three datasets (Inria aerial dataset, international society for photogrammetry and remote sensing Potsdam dataset, and UAV building dataset), to evaluate its accuracy and robustness. As a result, we found that PCL-PTD net can improve learning capacities of the supervised learning model in differentiating buildings in dense area and extracting buildings covered by shadows. As compared to the baseline networks, we found that proposed network shows superior performance compared to all eight networks (SegNet, U-net, pyramid scene parsing network, PixelDCL, DeeplabV3+, U-Net++, context feature enhancement networ, and improved ResU-Net). The experiments on three datasets also demonstrate the ability of proposed framework and indicating its performance.
Some of the metrics are blocked by your
consent settings
Deep neural learning adaptive sequential monte carlo for automatic image and speech recognition
(2020-01-01)
Kamsing, Patcharin
;
Torteeka, Peerapong
;
Boonpook, Wuttichai
;
Cao, Chunxiang
To enhance the performance of image classification and speech recognition, the optimizer is considered an important factor for achieving high accuracy. The state-of-the-art optimizer can perform to serve in applications that may not require very high accuracy, yet the demand for high-precision image classification and speech recognition is increasing. This study implements an adaptive method for applying the particle filter technique with a gradient descent optimizer to improve model learning performance. Using a pretrained model helps reduce the computational time to deploy an image classification model and uses a simple deep convolutional neural network for speech recognition. The applied method results in a higher speech recognition accuracy score - 89.693% for the test dataset - than the conventional method, which reaches 89.325%. The applied method also performs well on the image classification task, reaching an accuracy of 89.860% on the test dataset, better than the conventional method, which has an accuracy of 89.644%. Despite a slight difference in accuracy, the applied optimizer performs well in this dataset overall.
Some of the metrics are blocked by your
consent settings
Aircraft trajectory recognition via statistical analysis clustering for Suvarnabhumi International Airport
(2020-02-01)
Kamsing, Patcharin
;
Torteeka, Peerapong
;
Yooyen, Soemsak
;
Yenpiem, Siriporn
;
Delahaye, Daniel
Since Suvarnabhumi International Airport is considered to be the biggest airport in Thailand, a big travelling-hub of southeast Asia and plays a significant part to the economy of Thailand relying on the tourism industry, an aircraft trajectory recognition is essential to support the high traffic management system from around the world. The first and essential stage of airport capacity enhancement is descriptive-analytic in several sections of the airport, including flight trajectory behaviors in order to plan an improvement procedure in the future. This experiment deploys K-mean and Gaussian Mixture clustering to compare results by using available automatic dependent surveillance-broadcast (ADS-B) dataset provided by the bigdata system from various websites. The test varies the number of clustering from three to ten and measures how similar an object is to its cluster by using the Silhouette score. Gaussian Mixture clustering produces at least three unique flight trajectories when setting the number of clustering equal to four, giving the Silhouette score of 0.43. K-mean clustering with the number of clustering equal to ten gives the highest Silhouette score of 0.45. However, its routes are not clearly recognized when compared with the Gaussian Mixture clustering. Although the overall results are not clearly shown in the pattern, it is enough to describe the trajectory patterns of the aircrafts taking off or landing over Suvarnabhumi International Airport.
Some of the metrics are blocked by your
consent settings
Ground software architecture for a lunar particle detector: Implementation with a double-sided silicon strip detector
(2026-04-15)
Panyalert, Thanayuth
;
Manuthasna, Shariff
;
Torteeka, Peerapong
;
He, Xu
;
Zhang, Ning
The Moon-Aiming Thai-Chinese Hodoscope (MATCH) is a particle detector developed for the Chang’E-7 mission, designed to support space weather monitoring and cosmic radiation studies within the Sun-Earth-Moon system. The primary observational objectives of MATCH include space weather science and alerts, as well as the detection of cosmic radiation, particularly Jovian and Galactic Cosmic Ray (GCR) electrons. Additionally, MATCH can detect lunar albedo ions (alpha particles and protons) and contribute to understanding cosmic-ray interactions with the lunar surface, including high-energy particle backscattering mechanisms. These studies are essential for improving our knowledge of cosmic ray propagation and energy distribution in the lunar environment. MATCH integrates a double-sided silicon strip detector (DSSD) for precise position tracking of incoming particles, along with a bismuth germanate (BGO) scintillator stack for accurate energy measurements. This study presents the development and validation of a scalable ground software architecture that supports event detection, signal processing, and data calibration, optimized for constrained onboard resources. The system has been validated through hardware-in-the-loop (HIL) testing using alpha-emitting sources under mission-equivalent conditions, demonstrating high accuracy and resource efficiency for on-orbit data acquisition modes. Once deployed, MATCH is expected to provide the first continuous MeV-range cosmic electron measurements from lunar orbit, enabling new insights into Jovian and Galactic cosmic ray propagation, space weather variability, and lunar albedo ion generation. The software architecture developed here plays a critical role in enabling astrophysical investigations during the upcoming Chang’E-7 mission.
Some of the metrics are blocked by your
consent settings
Cooperative motion planning for multiple uavs via the bezier curve guided line of sight techniques
(2021-02-07)
Hematulin, Warunyu
;
Kamsing, Patcharin
;
Torteeka, Peerapong
;
Somjit, Thanaporn
;
Phisannupawong, Thaweerath
Multiple motion planning plays an essential role in several vehicle motions. This paper proposes a cooperative method between the Line of Sight techniques and the Bezier curve, applying this to motion planning for unmanned aerial vehicles. The experiment is implemented using the AirSim plugin on Unreal Engine 4. The results of the proposed method are compared with those for the conventional Line of Sight techniques to control multiple unmanned aerial vehicles. The results illustrate that the proposed method takes more time to process than the conventional one. However, the proposed method can reach a higher performance by addressing the target unmanned aerial vehicles and the pre-defining path more than the conventional method does, which is shown in all three simulation cases.
Some of the metrics are blocked by your
consent settings
Sustainable Urban Healthcare Accessibility: Voronoi Screening and Travel-Time Coverage in Bangkok
(2025-12-01)
Boonprong, Sornkitja
;
Punturasan, Nathapat
;
Kamsing, Patcharin
;
Torteeka, Peerapong
;
Cao, Chunxiang
This study presents an integrated and reproducible framework for within-tier screening of potential healthcare accessibility in Bangkok. Facilities in three service tiers (primary 294 units, regular 75, referral 29) are analyzed using point-pattern diagnostics, Voronoi geometric partitions, population-weighted allocation from subdistrict controls, and cumulative network travel-time isochrones. Spatial diagnostics indicate clustering among primary care units, a near-random configuration for regular units, and modest dispersion for referral hospitals, summarized by observed-to-expected nearest-neighbor ratios of approximately 0.77, 1.05, and 1.19, respectively. Voronoi partitions translate these distributions into geometric units that enlarge with increasing inter-facility spacing, while population-weighted assignments reveal higher population-per-partition-area burdens in the outer east and southwest. Isochrone maps (5–60 min rings) show central corridors with short travel times and peripheral areas where potential access declines. Interpreted against statutory planning intent, the maps indicate broad consistency of siting with high-intensity zones, alongside residual gaps at residential fringes. Framed as repeatable indicators of access and coverage, the workflow contributes to measuring and monitoring urban health sustainability under universal health coverage and routine planning cycles. The framework yields transparent indicators that support monitoring, priority setting, and incremental adjustments within each tier. Limitations include planar proximity assumptions, uniform areal weighting, single-mode modeled travel times without temporal variation, and the absence of capacity measures, motivating future work on capacity-weighted partitions, minimal dasymetric refinements, and time-dependent multimodal scenarios.
Some of the metrics are blocked by your
consent settings
Hardware-in-the-Loop Simulation Testbed for Three-Axis Earth's Magnetic Field Generation Based on 2.4- Meter Square Helmholtz Coils
(2023-01-01)
Chaisakulsurin, Jormpon
;
Manuthasna, Shariff
;
Masri, Tanawish
;
Panyalert, Thanayuth
;
Palee, Kritsada
This paper proposes a Hardware-in-the-Loop sim-ulation (HiLs) tested via square Helmholtz coils as a relative magnetic field generator. In technical terms, the HiLs is an indispensable tool for engineering design during rapid proto-typing of attitude determination and control algorithms for the turning parameters that control the attitude of the satellite, since most of the satellite's mission relies on its attitude, making this system one of the most essential to the satellite's operation. More-over, performing controlled experiments with the parameters for developing adaptive control algorithms improves the overall efficiency of the satellite's kinematic system. The conceptual design of a proposed system architecture can be composed of the electrical currents of 2.4-meter square Helmholtz coils produced by a low-level microcontroller equipped with a DC-motor driver by a pulse-width modulation (PWM) signal through real-time connection to an orbit propagator using a high-level computer. This research focuses on the attitude dynamic of satellites through the interaction between the Earth's magnetic field (EMF) and the magnetotorque in the satellite. To apply this phenomenon, the intensity and the direction of the magnetic field must be identified through Biot-Savart's law. Along with the EMF, the reference position is calculated using the standard general perturbations satellite orbit model (SGP4), and the intensity is modeled based on coefficients from the 13th edition of the International Geo-magnetic Reference Field (IGRF). Therefore, this paper presents a detailed development of a HiLs testbed for distributed attitude determination and control systems (hardware and software co-design, protocol, and control theory). Furthermore, it discusses a classic cooperative control case for the output of magnetic field intensity and direction, which was undertaken to explain the integrated simulation process and validate the effectiveness of the co-simulation tested to be a primary experiment.
Some of the metrics are blocked by your
consent settings
Optimization based telescope passive auto-focusing through image quality assessment for Thai National Space object Observation
(2022-01-01)
Torteeka, Peerapong
;
Anutarawiramkul, Rungrit
;
Butpan, Pathompong
;
Palee, Kritsada
;
Prasit, Pakawat
The coming years, the growth of orbital debris in the Resident of Space Objects (RSOs) could be a serious issue for operational spacecraft and manned spaceflight. To prevent debris-related risks in operational orbit, a ground-based passive optical telescope was used as a fundamental imaging sensor for Space Situation Awareness to periodically maintain the orbital parameters of a space object in RSOs through an astrometry engineering approach. In the case of a small and dim space object, it produces low contrast images and suffers from a lack of sharpness which are easily influenced by background interference. Normally, a manual adjustment of a preliminary focus range of the telescope is one of the tedious practices that astronomers constantly face for the high-contrast image capturing before beginning a tracking procedure. Therefore, the passive automatic focusing process was initially required for a robotic telescope as a function of image quality assessment. Technically, the auto-focusing is a combination of processes between software and motorized focusing hardware with position feedback. In this paper, we investigate a new approach and software for passive automatic focusing charge-coupled device based telescope systems for finding a focal-point of an imaging system that minimizes objectives while satisfying constraints. These systems are most appropriate for unobserved all-night telescope operations as an asteroid and/or orbital debris monitoring. Based on the image quality assessment, a function of Full-Width Half Maximum was applied, the auto-focusing algorithm of the telescope system was realized via the golden section optimizer through the least square method. The experimental results were obtained during the commissioning of an alt-azimuth mounting equipped with a 0.7-meter optical aperture telescope from two observation sites at the National Astronomical Research Institute of Thailand. Two state-of-the-art methods were used for demonstrating and presenting method efficiency. Final results denote that the presented proposed algorithm improves the quality of the image contrast and can provide clearer details and information.
Some of the metrics are blocked by your
consent settings
Wi-Fi Received Signal Strength-based Indoor Localization System Using K-Nearest Neighbors fingerprint integrated D∗algorithm
(2022-01-01)
Jarawan, Tanatthep
;
Kamsing, Patcharin
;
Torteeka, Peerapong
;
Manuthasna, Shariff
;
Hematulin, Warunyu
The indoor localization system is essential since the Global Positioning System cannot give an accurate position indoors, especially when several floor plans are considered. WiFi received signal strength becomes an alternative indicator for indoor localization systems. The experiment proposed a localization system created by integrating and working between the K-Nearest Neighbors algorithm and the D∗algorithm. The result illustrates the optimal path from the start point to the target point by avoiding the obstacle performing exceptionally well. The K-Nearest Neighbors algorithm provide the result for localization with Root Mean Square Errors of displacement at 1.190 meters, 2.491 meters, and 1.363 meters of X-Axis Y-Axis, respectively. The proposed indoor localization system can have various applications considering different environmental factors in different applications, such as the size of unmanned aerial vehicles when applying indoor unmanned aerial vehicles.
Some of the metrics are blocked by your
consent settings
Multi-UAV Standoff Tracking in Unknown Complex Environments Using a Modulated Adaptive Guiding Vector Field
(2026-03-01)
Chen, Guodong
;
Yuan, Shuai
;
Liu, Jingzong
;
Zhang, Zexu
;
Kamsing, Patcharin
This paper proposes a novel trajectory planning method for multiple UAVs (Unmanned Aerial Vehicle, UAV) collaborative standoff tracking using a consistency GVF (Guiding Vector Field, GVF) with an adaptive gain (AG-GVF), which is modulated by a modulation matrix for collision-free navigation in unknown complex environments. Firstly, the AG-GVF is established based on the desired path, with an adaptive gain and an additional virtual coordinate introduced to elevate dimensionality. The adaptive gain aims at reducing steady-state error and eliminating oscillations. This virtual coordinate is not only used for eliminating singular points but also utilized as a state variable for consistency control, ensuring uniform phase distribution among multiple UAVs during standoff tracking. Subsequently, in environments with obstacles, a modulation matrix is proposed to adjust the original GVF motion by estimating the normals of unknown obstacles using point clouds and constructing a modulation matrix to modify the AG-GVF direction for effective obstacle avoidance. Finally, the obtained desired path is optimized to generate flight trajectories that satisfy the kinematic constraints of fixed-wing UAVs. Simulation results demonstrate that the proposed method enables multiple UAVs to achieve collaborative standoff tracking with collision-free navigation in unknown complex environments.

Torteeka, Peerapong

Filters

Settings

Sort By

Results per page