Unveiling the Urban Morphology of Small Towns in the Eastern Qinba Mountains: Integrating Earth Observation and Morphometric Analysis DOI Creative Commons
Xin Zhao,

Zuobin Wu

Buildings, Год журнала: 2024, Номер 14(7), С. 2015 - 2015

Опубликована: Июль 2, 2024

In the context of current information age, leveraging Earth observation (EO) technology and spatial analysis methods enables a more accurate understanding characteristics small towns. This study conducted an in-depth urban morphology towns in Qinba Mountain Area Southern Shaanxi by employing large-scale data innovative form measurement methods. The U-Net3+ model, based on deep learning technology, combined with concave hull algorithm, was used to extract precisely define boundaries 31,799 buildings morphological town core were measured, areas defined using calculated tessellation cells. Hierarchical clustering applied analyze 12 characteristic indicators 89 towns, various metrics determine optimal number clusters. identified eight distinct clusters towns’ differences. Significant differences between observed. results revealed that exhibited diverse shapes distributions, ranging from irregular sparse compact dense forms, reflecting layout patterns influenced unique each town. use morphometric method, cellular biological morphometry, provided new perspective deepened structure micro perspective. These findings not only contribute development quantitative for planning but also demonstrate novel, data-driven approach conventional studies.

Язык: Английский

Case Studies on Generative Adversarial Networks in Precision Farming DOI

Pradnya L. Awate,

Ajay D. Nagne

Advances in geospatial technologies book series, Год журнала: 2025, Номер unknown, С. 291 - 320

Опубликована: Апрель 30, 2025

The chapter reviews the applicability of Generative Adversarial Networks in precision agriculture, with an emphasis on its role enhancing remote sensing technology. This ranges from resolution augmentation for satellite and drone images using GAN-based models like SRGAN CycleGAN to generating synthetic data training that will help crop health monitoring, soil analysis, yield prediction. case study demonstrates tremendous improvements image quality decision-making, further reach into weather simulation, real-time UAV IoT integration.

Язык: Английский

Процитировано

0
Single-Shot X-ray to Multi-View Projections for 3D Pork Shoulder Bone Analysis DOI

Michiel Pieters,

Pieter Verboven, Bart Nicolaı̈

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Май 22, 2025

Abstract Pork is an important meat product for the European Union, which exported over 4.2 million tons in 2023, valued at €8.1 billion. Automating labor-intensive deboning process of significant interest, particularly through development advanced inline inspection systems capable analyzing pork shoulder bone structures. While computed tomography (CT) provide high-contrast 3D reconstructions, their large size and high-cost present substantial barriers to adoption industrial processing. This study addresses these challenges by introducing a novel approach that uses single X-ray projection combination with deep neural networks predict segmentation map structures using conventional reconstruction algorithms. To this end, U-Net network variants were trained on high-resolution CT scans 90 shoulders. These augmented synthetic data simulate different orientations conveyor belt, ensuring model’s robustness. The minimum number projections needed accurate was determined based simulations, 60 evenly spaced between 0° 180° found optimal. Feldkamp-Davis-Kress (FDK) algorithm chosen its efficiency cost-effectiveness model achieved Dice score 0.94 SSIM 0.96 test data, demonstrating ability 59 missing reconstruct structure accurately. method proposed paper has potential advance processing enhancing precision, reducing waste, streamlining operations.

Язык: Английский

Процитировано

0
Improving Non-Line-of-Sight Identification in Cellular Positioning Systems Using a Deep Autoencoding and Generative Adversarial Network Model DOI Creative Commons
Yanbiao Gao, Zhongliang Deng,

Yuqi Huo

и другие.

Sensors, Год журнала: 2024, Номер 24(19), С. 6494 - 6494

Опубликована: Окт. 9, 2024

Positioning service is a critical technology that bridges the physical world with digital information, significantly enhancing efficiency and convenience in life work. The evolution of 5G has proven positioning services are integral components current future cellular networks. However, accuracy hindered by non-line-of-sight (NLoS) propagation, which severely affects measurements angles delays. In this study, we introduced deep autoencoding channel transform-generative adversarial network model utilizes line-of-sight (LoS) samples as singular category training set to fully extract latent features LoS, ultimately employing discriminator an NLoS identifier. We validated proposed indoor factory (dense clutter, low base station) scenarios assessing its generalization capability across different scenarios. results indicate that, compared state-of-the-art method, markedly diminished utilization device resources achieved 2.15% higher area under curve while reducing computing time 12.6%. This approach holds promise for deployment terminals achieve superior localization precision, catering commercial industrial Internet Things applications.

Язык: Английский

Процитировано

2
Unveiling the Urban Morphology of Small Towns in the Eastern Qinba Mountains: Integrating Earth Observation and Morphometric Analysis DOI Creative Commons
Xin Zhao,

Zuobin Wu

Buildings, Год журнала: 2024, Номер 14(7), С. 2015 - 2015

Опубликована: Июль 2, 2024

In the context of current information age, leveraging Earth observation (EO) technology and spatial analysis methods enables a more accurate understanding characteristics small towns. This study conducted an in-depth urban morphology towns in Qinba Mountain Area Southern Shaanxi by employing large-scale data innovative form measurement methods. The U-Net3+ model, based on deep learning technology, combined with concave hull algorithm, was used to extract precisely define boundaries 31,799 buildings morphological town core were measured, areas defined using calculated tessellation cells. Hierarchical clustering applied analyze 12 characteristic indicators 89 towns, various metrics determine optimal number clusters. identified eight distinct clusters towns’ differences. Significant differences between observed. results revealed that exhibited diverse shapes distributions, ranging from irregular sparse compact dense forms, reflecting layout patterns influenced unique each town. use morphometric method, cellular biological morphometry, provided new perspective deepened structure micro perspective. These findings not only contribute development quantitative for planning but also demonstrate novel, data-driven approach conventional studies.

Язык: Английский

Процитировано

0