Relevant bibliographies by topics / PSPNet

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'PSPNet'

Author: Grafiati
Published: 25 June 2021
Last updated: 21 June 2025

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Journal articles on the topic "PSPNet"

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Yuan, Wei, Jin Wang, and Wenbo Xu. "Shift Pooling PSPNet: Rethinking PSPNet for Building Extraction in Remote Sensing Images from Entire Local Feature Pooling." Remote Sensing 14, no. 19 (2022): 4889. http://dx.doi.org/10.3390/rs14194889.

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Building extraction by deep learning from remote sensing images is currently a research hotspot. PSPNet is one of the classic semantic segmentation models and is currently adopted by many applications. Moreover, PSPNet can use not only CNN-based networks but also transformer-based networks as backbones; therefore, PSPNet also has high value in the transformer era. The core of PSPNet is the pyramid pooling module, which gives PSPNet the ability to capture the local features of different scales. However, the pyramid pooling module also has obvious shortcomings. The grid is fixed, and the pixels
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Li, Yuxia, Peng Li, Hailing Wang, Xiaomei Gong, and Zhijun Fang. "CAML-PSPNet: A Medical Image Segmentation Network Based on Coordinate Attention and a Mixed Loss Function." Sensors 25, no. 4 (2025): 1117. https://doi.org/10.3390/s25041117.

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The problems of missed segmentation with fuzzy boundaries of segmented regions and small regions are common in segmentation tasks, and greatly decrease the accuracy of clinicians’ diagnosis. For this, a new network based on PSPNet, using a coordinate attention mechanism and a mixed loss function for segmentation (CAML-PSPNet), is proposed. Firstly, the coordinate attention module splits the input feature map into horizontal and vertical directions to locate the edge position of the segmentation target. Then, a Mixed Loss function (MLF) is introduced in the model training stage to solve the pro
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McCall, Hugh, and Heather Hadjistavropoulos. "Online Therapy to Treat Mental Health Concerns Among Police and Other Public Safety Personnel." Applied Police Briefings 1, no. 2 (2024): 25–27. http://dx.doi.org/10.22215/apb.v1i2.5011.

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PSPNET is a research unit at the University of Regina in Saskatchewan, Canada, that provides free online therapy programs to Canadian first responders and other public safety personnel (PSP). The first 560 clients (33% police) in PSPNET’s most popular therapy program—an internet-delivered cognitive behavioural therapy (ICBT) program called the PSP Wellbeing Course—have shown large improvements in mental health, as well as good satisfaction and engagement with the program. Treatment outcomes were similar for different groups of clients (e.g., men and women, clients in different occupational gro
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Zhao, Jinling, Zheng Li, Yu Lei, and Linsheng Huang. "Application of UAV RGB Images and Improved PSPNet Network to the Identification of Wheat Lodging Areas." Agronomy 13, no. 5 (2023): 1309. http://dx.doi.org/10.3390/agronomy13051309.

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As one of the main disasters that limit the formation of wheat yield and affect the quality of wheat, lodging poses a great threat to safety production. Therefore, an improved PSPNet (Pyramid Scene Parsing Network) integrating the Normalization-based Attention Module (NAM) (NAM-PSPNet) was applied to the high-definition UAV RGB images of wheat lodging areas at the grain-filling stage and maturity stage with the height of 20 m and 40 m. First, based on the PSPNet network, the lightweight neural network MobileNetV2 was used to replace ResNet as the feature extraction backbone network. The deep s
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Yang, Chengzhi, and Hongjun Guo. "A Method of Image Semantic Segmentation Based on PSPNet." Mathematical Problems in Engineering 2022 (August 9, 2022): 1–9. http://dx.doi.org/10.1155/2022/8958154.

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Image semantic segmentation is a visual scene understanding task. The goal is to predict the category label of each pixel in the input image, so as to achieve object segmentation at the pixel level. Semantic segmentation is widely used in automatic driving, robotics, medical image analysis, video surveillance, and other fields. Therefore, improving the effect and accuracy of image semantic segmentation has important theoretical research significance and practical application value. This paper mainly introduces the pyramid scene parsing network PSPNet based on pyramid pooling and proposes a par
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Gao, Jianqin, and Kaihua Cui. "Coal Image Recognition Method Based on Improved Semantic Segmentation Model of PSPNET Network." Modern Applied Science 17, no. 2 (2023): 1. http://dx.doi.org/10.5539/mas.v17n2p1.

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To implement the intelligence and automation of coal mines, coal recognition plays a crucial role. In order to further improve the accuracy and speed of intelligent coal recognition, this paper proposes a semantic segmentation model based on an improved PSPNET network. (1) The lightweight MobilenetV2 module is used as the backbone feature extraction network. Compared to traditional networks, it has fewer parameters while achieving higher recognition accuracy and speed.(2) The Convolutional Block Attention Module (CBAM) is introduced into the Pyramid Pooling Module (PPM) to enhance the network&
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Gumus, Kazim Z., Julien Nicolas, Dheeraj R. Gopireddy, Jose Dolz, Seyed Behzad Jazayeri, and Mark Bandyk. "Deep Learning Algorithms for Bladder Cancer Segmentation on Multi-Parametric MRI." Cancers 16, no. 13 (2024): 2348. http://dx.doi.org/10.3390/cancers16132348.

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Background: Bladder cancer (BC) segmentation on MRI images is the first step to determining the presence of muscular invasion. This study aimed to assess the tumor segmentation performance of three deep learning (DL) models on multi-parametric MRI (mp-MRI) images. Methods: We studied 53 patients with bladder cancer. Bladder tumors were segmented on each slice of T2-weighted (T2WI), diffusion-weighted imaging/apparent diffusion coefficient (DWI/ADC), and T1-weighted contrast-enhanced (T1WI) images acquired at a 3Tesla MRI scanner. We trained Unet, MAnet, and PSPnet using three loss functions: c
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Qiao, Yichen, Yaohua Hu, Zhouzhou Zheng, et al. "A Diameter Measurement Method of Red Jujubes Trunk Based on Improved PSPNet." Agriculture 12, no. 8 (2022): 1140. http://dx.doi.org/10.3390/agriculture12081140.

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A trunk segmentation and a diameter measurement of red jujubes are important steps in harvesting red jujubes using vibration harvesting robots as the results directly affect the effectiveness of the harvesting. A trunk segmentation algorithm of red jujubes, based on improved Pyramid Scene Parsing Network (PSPNet), and a diameter measurement algorithm to realize the segmentation and diameter measurement of the trunk are proposed in this research. To this end, MobilenetV2 was selected as the backbone of PSPNet so that it could be adapted to embedded mobile applications. Meanwhile, the Convolutio
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Oppong, Judith N., Clement E. Akumu, Samuel Dennis, and Stephanie Anyanwu. "Examining Deep Learning Pixel-Based Classification Algorithms for Mapping Weed Canopy Cover in Wheat Production Using Drone Data." Geomatics 5, no. 1 (2025): 4. https://doi.org/10.3390/geomatics5010004.

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Deep learning models offer valuable insights by leveraging large datasets, enabling precise and strategic decision-making essential for modern agriculture. Despite their potential, limited research has focused on the performance of pixel-based deep learning algorithms for detecting and mapping weed canopy cover. This study aims to evaluate the effectiveness of three neural network architectures—U-Net, DeepLabV3 (DLV3), and pyramid scene parsing network (PSPNet)—in mapping weed canopy cover in winter wheat. Drone data collected at the jointing and booting growth stages of winter wheat were used
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Khadijah, Nur Endah Sukmawati, Kusumaningrum Retno, Rismiyati, Sidik Sasongko Priyo, and Zainan Nisa Iffa. "Solid waste classification using pyramid scene parsing network segmentation and combined features." TELKOMNIKA (Telecommunication, Computing, Electronics and Control) 19, no. 6 (2021): 1902–12. https://doi.org/10.12928/telkomnika.v19i6.18402.

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Solid waste problem become a serious issue for the countries around the world since the amount of generated solid waste increase annually. As an effort to reduce and reuse of solid waste, a classification of solid waste image is needed to support automatic waste sorting. In the image classification task, image segmentation and feature extraction play important roles. This research applies recent deep leaning-based segmentation, namely pyramid scene parsing network (PSPNet). We also use various combination of image feature extraction (color, texture, and shape) to search for the best combinatio
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Dissertations / Theses on the topic "PSPNet"

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von, Koch Christian, and William Anzén. "Detecting Slag Formation with Deep Learning Methods : An experimental study of different deep learning image segmentation models." Thesis, Linköpings universitet, Datorseende, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177269.

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Image segmentation through neural networks and deep learning have, in the recent decade, become a successful tool for automated decision-making. For Luossavaara-Kiirunavaara Aktiebolag (LKAB), this means identifying the amount of slag inside a furnace through computer vision.  There are many prominent convolutional neural network architectures in the literature, and this thesis explores two: a modified U-Net and the PSPNet. The architectures were combined with three loss functions and three class weighting schemes resulting in 18 model configurations that were evaluated and compared. This thes
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Smith, Anthony. "An investigation of the region of DNA required for Streptocymes Penemafaciens plasmid pSPN1 replication." Master's thesis, University of Cape Town, 1991. http://hdl.handle.net/11427/22128.

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Plasmid pSPNl is a 26.5kb cryptic plasmid, originally isolated from Streptomyces penemafaciens ATCC 31599. A 12.5kb BglII fragment of pSPNl was cloned into the vector pLR2, and this conferred on pLR2 which lacks a Streptomyces origin of replication, the ability to replicate in a number of Streptomyces species. A vector pBlue was constructed by inserting a streptomycin resistance gene from plasmid pIJ4642 into the ampicillin resistance gene of the vector Bluescript. The resistance gene was able to function in both E.coli and Streptomyces species and thus pBlue could serve as a vector for shorte
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Cheng, Hui. "Characterization of PspE, a Secreted Sulfurtransferase of Escherichia coli." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/32364.

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PspE, encoded by the last gene of the phage shock protein operon, is one of the nine proteins of Escherichia coli that contain a rhodanese homology domain. PspE is synthesized as a precursor with a 19-amino acid signal sequence and secreted to the periplasm. Mature PspE is the smallest rhodanese of E. coli (85 amino acids) and catalyzes the transfer of sulfur from thiosulfate to cyanide forming thiocyanate and sulfite. Cation exchange chromatography of a freeze-thaw extract of a PspE-overexpressing strain yielded two major peaks of active, homogeneous PspE. The two peaks contained two form
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Mano, Julia Miranda. "Implementação do PSPN e suas relações com a qualidade da educação infantil: o caso de um município no interior paulista." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/59/59140/tde-07082018-140015/.

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Este trabalho teve como objetivo analisar a trajetória de implementação da Lei nº 11.738, a Lei do Piso (PSPN) no contexto de um município paulista e suas relações com a qualidade da Educação Infantil. Assim, procuramos construir análises sobre como se deu o processo de implementação da lei na localidade e como se relacionou com a valorização docente e com a qualidade da Educação Infantil, refletindo sobre a congruência entre a valorização profissional docente e as condições necessárias à gestão democrática da escola. A construção dos dados foi realizada com base em documentos que tratassem a
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SILVA, Afonso Rodrigues da. "As implicações do PSPN para a carreira e a remuneração do magistério da rede municipal de Barcarena-Pa." Universidade Federal do Pará, 2017. http://repositorio.ufpa.br/jspui/handle/2011/9493.

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Submitted by Rose Suellen (rosesuellen@ufpa.br) on 2018-02-26T12:22:44Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_ImplicacoesPspnCarreira.pdf: 2227196 bytes, checksum: 59e7f4279c7ce7b425d84130f578295a (MD5)<br>Approved for entry into archive by Rose Suellen (rosesuellen@ufpa.br) on 2018-02-26T12:23:41Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_ImplicacoesPspnCarreira.pdf: 2227196 bytes, checksum: 59e7f4279c7ce7b425d84130f578295a (MD5)<br>Made available in DSpac
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Verçosa, Pelegrino Santos. "Remuneração do magistério estadual da educação básica do Acre : implicações da política de fundos, do PSPN e de alterações na legislação local." reponame:Repositório Institucional da UFPR, 2016. http://hdl.handle.net/1884/47896.

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Orientador: Prof. Dr. Marcos Edgar Bassi<br>Tese (doutorado) - Universidade Federal do Paraná, Setor de Educação, Programa de Pós-Graduação em Educação. Defesa: Curitiba, 22/03/2016<br>Inclui referências : f. 202-218<br>Resumo: A remuneração do magistério público ganhou espaço na agenda pública nos últimos anos, especialmente após a política de fundos de financiamento da educação básica inaugurada com o Fundo de Desenvolvimento do Ensino Fundamental e Valorização do Magistério (FUNDEF), substituído a partir de 2007 pelo Fundo de Desenvolvimento da Educação Básica e Valorização dos Profissionai
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Xavier, Raimundo Rainero. "A instituição do Piso Salarial Profissional Nacional (PSPN) por meio da Lei 11.738/2008 valoriza os professores do magistério da educação básica?" reponame:Repositório Institucional da UnB, 2015. http://dx.doi.org/10.26512/2015.10.D.18937.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Educação, Departamento de Pós-Graduação, Mestrado Profissional em Educação, 2015.<br>Submitted by Raquel Viana (raquelviana@bce.unb.br) on 2015-11-26T17:44:28Z No. of bitstreams: 1 2015_RaimundoRaineroXavier.pdf: 1500756 bytes, checksum: c976983076ebf3e4d4adac2fc1c438eb (MD5)<br>Approved for entry into archive by Raquel Viana(raquelviana@bce.unb.br) on 2015-12-16T17:33:04Z (GMT) No. of bitstreams: 1 2015_RaimundoRaineroXavier.pdf: 1500756 bytes, checksum: c976983076ebf3e4d4adac2fc1c438eb (MD5)<br>Made available in DSpace on 2015-
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Melo, Amilka Dayane Dias. "O vencimento dos profissionais do magist?rio da rede p?blica estadual de ensino do RN (2008-2014): a implementa??o do PSPN - Lei n? 11.738/2008." PROGRAMA DE P?S-GRADUA??O EM EDUCA??O, 2016. https://repositorio.ufrn.br/jspui/handle/123456789/21581.

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Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-01-03T19:53:02Z No. of bitstreams: 1 AmilkaDayaneDiasMelo_DISSERT.pdf: 8582091 bytes, checksum: a78ec666d0a3d06d1308e15e43ca615f (MD5)<br>Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-01-05T21:54:59Z (GMT) No. of bitstreams: 1 AmilkaDayaneDiasMelo_DISSERT.pdf: 8582091 bytes, checksum: a78ec666d0a3d06d1308e15e43ca615f (MD5)<br>Made available in DSpace on 2017-01-05T21:54:59Z (GMT). No. of bitstreams: 1 AmilkaDayaneDiasMelo_DISSERT.pdf: 8582091 bytes, checksum: a78ec666d0a3d06d1
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Hanna, Sharon. "Perceived Efficacies of Australian Paediatric Surgical Care by Rural and Metropolitan Paediatric Patients and their Parents." Thesis, Griffith University, 2013. http://hdl.handle.net/10072/366663.

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This study is the first to generate two patient satisfaction instruments, the Paediatric Surgical Patient Evaluation Questionnaire (PSPEQ, Parent form) and the Questionnaire on Children’s Surgery in Hospital (QCSH, Child form), with robust preliminary psychometric properties that capture the experiences of 5 to 10-year-old paediatric day-surgery patients and their parents in rural and metropolitan Australia. Patients’ and parents’ evaluations of Australian paediatric specialist surgical care and the impact of travel time on these evaluations was also newly investigated. The theoretical structu
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Sladký, Roman. "Techniky pro porovnávání biologických sekvencí." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235890.

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This work presents the building up of basic biological units DNA, RNA and proteins as well as their function. Provided data are kept in biological databases which are connected worldwide to supply preferable communication along with all kinds of available information to be used in the scientific research. The secret of alive is hidden in genes coded in sequences of nucleotides. Genes enable the creation of proteins which are made of sequences of amino-acids. The wide-spread methods of comparing these sequences are FASTA and BLAST algorithms. Their base is used for the PSProt program which is d
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Books on the topic "PSPNet"

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Child Development: Perspectives with Inst Psprt. Houghton Mifflin Company, 1999.

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Gonçalves, Patrícia, and Ana Jacinta Soares. From Particle Systems to Partial Differential Equations: PSPDE IV, Braga, Portugal, December 2015. Springer, 2018.

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Gonçalves, Patrícia, and Ana Jacinta Soares. From Particle Systems to Partial Differential Equations: PSPDE IV, Braga, Portugal, December 2015. Springer, 2017.

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From Particle Systems to Partial Differential Equations: PSPDE V, Braga, Portugal, November 2016. Springer, 2018.

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Book chapters on the topic "PSPNet"

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Chen, Ying, Lin Li, and Mei Huang. "An Algorithm for 3D Object Detection Based on Frustum-PSPNet." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-6203-5_83.

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Sarah, Heverton, Esteban Clua, and Cristina Nader Vasconcelos. "Arms and Hands Segmentation for Egocentric Perspective Based on PSPNet and Deeplab." In Virtual, Augmented and Mixed Reality. Design and Interaction. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49695-1_11.

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Ge, Jiangwei, Yan Li, Mengfei Jiu, Zichen Cheng, and Jingwei Zhang. "PFANet: A Network Improved by PSPNet for Semantic Segmentation of Street Scenes." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1260-5_16.

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Wu, Dikang, Jiamei Zhao, and Zhifang Wang. "AM-PSPNet: Pyramid Scene Parsing Network Based on Attentional Mechanism for Image Semantic Segmentation." In Communications in Computer and Information Science. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5194-7_32.

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Choure, Purvi, and Shaligram Prajapat. "Exploring U-Net, FCN, SegNet, PSPNet, Mask R-CNN and Using DeepLabV3+ for Multiclass Semantic Segmentation on Satellite Images of Western Ghats." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-74443-3_46.

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Gan, Vi Vi, Addie Irawan, Niirmel Ranjanendran, and Siti Noor Zuliana. "PSpHT-II: A Water Strider-Like Robot with Cylindrical Footpad." In Proceedings of the 10th National Technical Seminar on Underwater System Technology 2018. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3708-6_9.

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Ermolli, I., M. Fofi, C. Bernacchia, et al. "The Prototype RISE-PSPT Instrument Operating in Rome." In Solar Electromagnetic Radiation Study for Solar Cycle 22. Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5000-2_1.

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Wan Abdullah, Wan Aida Nadia, Naimah Yaakob, R. Badlishah Ahmad, Mohamed Elshaikh Elobaid, S. N. Azemi, and Siti Asilah Yah. "A PSPT-MAC Mechanism for Congestion Avoidance in Wireless Body Area Network." In Embracing Industry 4.0. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6025-5_6.

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Vogler, F. L., P. N. Brandt, W. Otruba, and A. Hanslmeier. "Center-to-Limb Variation of Facular Contrast Derived from MLSO RISE/PSPT Full Disk Images." In Solar Magnetic Phenomena. Springer Netherlands, 2005. http://dx.doi.org/10.1007/1-4020-2962-4_13.

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White, Oran R., Peter A. Fox, Randy Meisner, et al. "Data from the Precision Solar Photometric Telescope (PSPT) in Hawaii from March 1998 to March 1999." In Solar Variability and Climate. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-010-0888-4_7.

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Conference papers on the topic "PSPNet"

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Ding, Xinming, Lufeng Luo, Mingyou Chen, and Shaoming Luo. "BoT-PSPNet: bottleneck transformer enhanced PSPNet for fruit damage recognition and orchard monitoring." In International Conference on Optical and Photonic Engineering (icOPEN 2024), edited by Jianglei Di, Kemao Qian, Shijie Feng, et al. SPIE, 2025. https://doi.org/10.1117/12.3057850.

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Zhou, Shiqi, Weidong Song, and Shangyu Sun. "Building change detection based on improved PSPNet." In Sixth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2024), edited by Zhiliang Qin, Jun Chen, and Huaichun Wu. SPIE, 2025. https://doi.org/10.1117/12.3057650.

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Kim, Haerim, Ye Ju Kim, Junyoung Hong, Hyeri Yang, Shim Euna, and Kyungjae Lee. "Local Context Aggregation for Semantic Segmentation: A Novel PSPNet Approach." In 2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC). IEEE, 2024. http://dx.doi.org/10.1109/itc-cscc62988.2024.10628341.

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Jiang, Jieteng, and Huan Liu. "Semantic segmentation algorithm for remote sensing images based on PSPNet." In Third International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2024), edited by Kun Tan and Guobiao Yao. SPIE, 2025. https://doi.org/10.1117/12.3059422.

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Wang, Huihui, and Qiang Wang. "Ripnet: Real-Time Obstacle Detection for USVs Based on Improved PSPNet." In 2024 International Conference on Automation in Manufacturing, Transportation and Logistics (ICaMaL). IEEE, 2024. https://doi.org/10.1109/icamal62577.2024.10919594.

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Netrakar, Mohit, Dileep Upare, C. Tejas, Tarun Y. Baddi, and Rashmi Benni. "A Comparative Analysis of U-Net, PSPNet, AND FPNet: Deep Learning Techniques for Image Segmentation." In 2024 IEEE Conference on Engineering Informatics (ICEI). IEEE, 2024. https://doi.org/10.1109/icei64305.2024.10912308.

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Song, Pei, Xuefei Shi, Qi Xu, Jun Song, and Ziqi Xu. "Intelligent Detection and Risk Identification of Structural Surface Diseases Based on UAV." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.3250.

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&lt;p&gt;Traditional methods for detecting the disease of structural surface are time-consuming and labour- intensive, making it difficult to conduct comprehensive and accurate long-term monitoring. In this paper, highly maneuverable UAV with high positioning accuracy is used to efficiently collect images of the structural surface. Then, the ResNet model and PSPNet model are used to classify the images with disease and identify the morphology and location of the disease. Finally, based on the UAV’s positioning,the location information of the images is inversely solved to achieve the accurate l
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Seeli, D. Jeni Jeba, and K. K. Thanammal. "Brain Disease Detection using PSPNet for Multiclass Segmentation." In 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC). IEEE, 2023. http://dx.doi.org/10.1109/icaaic56838.2023.10140366.

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Zhou, Peng, and Kai Xiong. "Mars terrain segmentation algorithm based on improved PSPNet." In International Conference on Optics and Machine Vision (ICOMV 2023), edited by Jinping Liu. SPIE, 2023. http://dx.doi.org/10.1117/12.2678653.

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Xiang, Jie, and Rongshaung Fan. "A road extraction method based on improved PSPNet." In International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2023), edited by Chao Zuo. SPIE, 2023. http://dx.doi.org/10.1117/12.2682633.

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