default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMarcos Ricardo Omena de Albuquerque Máximo
Marcos Ricardo Omena Albuquerque Máximo – Marcos R. O. de A. Máximo – Marcos R. O. A. Máximo
Person information
- affiliation: Aeronautics Institute of Technology, São José dos Campos, Brazil
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j16]Henrique Mohallem Paiva
, Priscila Falcão dos Santos, Marcos Ricardo Omena Albuquerque Máximo, Lucas Niemeyer:
Efficient Lecturer Peer-Assessment Attribution Using Graph Theory and a Novel Greedy Algorithm. IEEE Access 12: 14742-14750 (2024)- [j15]Carolina Rutili de Lima, Said Ghani Khan, Muhammad Tufail, Syed Humayoon Shah, Marcos Ricardo Omena de Albuquerque Máximo:
Humanoid Robot Motion Planning Approaches: a Survey. J. Intell. Robotic Syst. 110(2): 86 (2024) - [j14]Francisco A. B. Azevedo, Guilherme P. C. Leão, Marcos Ricardo Omena de Albuquerque Máximo:
Neural Network Design for a Curved Kicking Mechanism with Obstacle Avoidance in RoboCup Small Size League (SSL). J. Intell. Robotic Syst. 110(3): 124 (2024) - [j13]Gabriel R. Pardini, Tahisa Neitzel Kuck, Elcio H. Shiguemori, Marcos R. O. A. Máximo, Gabriel Dietzsch, Pamela Molina:
Multistage Algorithm for Detecting Landing Strips in the Amazon Rainforest. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024) - [j12]Rafael Figueiredo Prudencio, Marcos Ricardo Omena Albuquerque Máximo, Esther Luna Colombini:
A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems. IEEE Trans. Neural Networks Learn. Syst. 35(8): 10237-10257 (2024) - [c47]Joao P. A. Dantas, Samara R. Silva, Vitor Conrado Faria Gomes, Andre N. Costa, Adrisson R. Samersla, Diego Geraldo, Marcos R. O. A. Máximo, Takashi Yoneyama:
AsaPy: A Python Library for Aerospace Simulation Analysis. SIGSIM-PADS 2024: 15-24 - [c46]Joao P. A. Dantas, Marcos R. O. A. Máximo, Takashi Yoneyama:
Loyal Wingman Assessment: Social Navigation for Human-Autonomous Collaboration in Simulated Air Combat. SIGSIM-PADS 2024: 61-62 - [i20]André O. Françani, Marcos R. O. A. Máximo:
Motion Consistency Loss for Monocular Visual Odometry with Attention-Based Deep Learning. CoRR abs/2401.10857 (2024) - [i19]Angelo Caregnato-Neto, Luciano Cavalcante Siebert, Arkady Zgonnikov, Marcos Ricardo Omena de Albuquerque Máximo, Rubens Junqueira Magalhães Afonso:
ARMCHAIR: integrated inverse reinforcement learning and model predictive control for human-robot collaboration. CoRR abs/2402.19128 (2024) - [i18]Joao P. A. Dantas, Marcos Ricardo Omena Albuquerque Máximo, Takashi Yoneyama:
Loyal Wingman Assessment: Social Navigation for Human-Autonomous Collaboration in Simulated Air Combat. CoRR abs/2405.00073 (2024) - [i17]Gabriel Adriano de Melo, Marcos Ricardo Omena de Albuquerque Máximo, Nei Yoshihiro Soma, Paulo André Lima de Castro:
On the Undecidability of Artificial Intelligence Alignment: Machines that Halt. CoRR abs/2408.08995 (2024) - 2023
- [j11]Jorge A. Ricardo, Luiz Giacomossi, João Francisco Silva Trentin, José F. B. Brancalion, Marcos Ricardo Omena de Albuquerque Máximo, Davi A. Santos:
Cooperative Threat Engagement Using Drone Swarms. IEEE Access 11: 9529-9546 (2023) - [j10]Angelo Caregnato-Neto, Marcos R. O. de A. Máximo, Rubens Junqueira Magalhães Afonso:
Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming. Adv. Robotics 37(5): 356-379 (2023) - [j9]Andre Silva, Alison de Oliveira Moraes, Jonas Sousasantos, Marcos R. O. A. Máximo, Bruno César Vani, Clodoaldo Faria:
Using Deep Learning to Map Ionospheric Total Electron Content over Brazil. Remote. Sens. 15(2): 412 (2023) - [c45]Angelo Caregnato-Neto, Marcos R. O. A. Máximo, Rubens Junqueira Magalhães Afonso:
A Novel Line of Sight Constraint for Mixed-Integer Programming Models with Applications to Multi-Agent Motion Planning. ECC 2023: 1-6 - [c44]Moisés J. S. Freitas, Alison de Oliveira Moraes, Emanoel Costa, Marcos Ricardo Omena de Albuquerque Máximo, Clodoaldo Faria:
Ionospheric scintillation simulation based on neural networks. EUROCON 2023: 84-88 - [c43]Michele Cipriano, Marcos R. O. A. Máximo, Nicola Scianca, Leonardo Lanari, Giuseppe Oriolo:
Feasibility-Aware Plan Adaptation in Humanoid Gait Generation. Humanoids 2023: 1-8 - [c42]Nathan A. Z. Xavier, Jonathan De A. Lapa, Douglas D. De C. Honório, Rafael C. De Oliveira, Elcio H. Shiguemori, Marcos R. O. A. Máximo, Marco Antonio Pizani Domiciano:
Comparison of Feature Extraction and Matching Techniques Applied to Monocular UAV Images With Low-quality and Land Cover Variations. LARS/SBR/WRE 2023: 47-52 - [c41]Thiago Filipe de Medeiros, Takashi Yoneyama, Marcos Ricardo Omena de Albuquerque Máximo:
Deep Reinforcement Learning Applied to IEEE's Very Small Size Soccer in Cooperative Attack Strategy. LARS/SBR/WRE 2023: 349-354 - [c40]André O. Françani, Marcos Ricardo Omena de Albuquerque Máximo:
Motion Consistency Loss for Monocular Visual Odometry with Attention-Based Deep Learning. LARS/SBR/WRE 2023: 409-414 - [c39]Otávio H. R. Guimarães, Marcos R. O. A. Máximo, José Maria Parente de Oliveira:
Comparison of Encoder-Decoder Networks for Soccer Field Segmentation. LARS/SBR/WRE 2023: 496-501 - [c38]Joao P. A. Dantas, Marcos R. O. A. Máximo, Takashi Yoneyama:
Autonomous Agent for Beyond Visual Range Air Combat: A Deep Reinforcement Learning Approach. SIGSIM-PADS 2023: 48-49 - [c37]Francisco Bruno Dias Ribeiro da Silva, Marcos Ricardo Omena de Albuquerque Máximo, Takashi Yoneyama, Davi Herculano Vasconcelos Barroso, Rodrigo Tanaka Aki:
Calibration of Inverse Perspective Mapping for a Humanoid Robot. RoboCup 2023: 117-128 - [c36]Davi M. Vasconcelos, Marcos R. O. A. Máximo, Paulo Marcelo Tasinaffo:
An Opponent Formation Classifier for Simulated Robot Soccer. RoboCup 2023: 179-190 - [c35]Eric Guerra Ribeiro, Marcos R. O. A. Máximo:
Orienting a Humanoid Robot in a Soccer Field Based on the Background. RoboCup 2023: 240-251 - [i16]Joao P. A. Dantas, Marcos R. O. A. Máximo, Takashi Yoneyama:
Autonomous Agent for Beyond Visual Range Air Combat: A Deep Reinforcement Learning Approach. CoRR abs/2304.09669 (2023) - [i15]André O. Françani, Marcos R. O. A. Máximo:
Transformer-based model for monocular visual odometry: a video understanding approach. CoRR abs/2305.06121 (2023) - [i14]Angelo Caregnato-Neto, Marcos Ricardo Omena de Albuquerque Máximo, Rubens Junqueira Magalhães Afonso:
A Mixed-Integer Approach for Motion Planning of Nonholonomic Robots under Visible Light Communication Constraints. CoRR abs/2306.15590 (2023) - [i13]Joao P. A. Dantas, Diego Geraldo, Andre N. Costa, Marcos Ricardo Omena Albuquerque Máximo, Takashi Yoneyama:
ASA-SimaaS: Advancing Digital Transformation through Simulation Services in the Brazilian Air Force. CoRR abs/2309.08680 (2023) - [i12]Joao P. A. Dantas, Samara R. Silva, Vitor Conrado Faria Gomes, Andre N. Costa, Adrisson R. Samersla, Diego Geraldo, Marcos R. O. A. Máximo, Takashi Yoneyama:
AsaPy: A Python Library for Aerospace Simulation Analysis. CoRR abs/2310.00001 (2023) - [i11]Joao P. A. Dantas, Diego Geraldo, Felipe L. L. Medeiros, Marcos R. O. A. Máximo, Takashi Yoneyama:
Real-Time Surface-to-Air Missile Engagement Zone Prediction Using Simulation and Machine Learning. CoRR abs/2311.11905 (2023) - 2022
- [j8]Bruno Brandão, Telma Woerle de Lima, Anderson Soares, Luckeciano C. Melo, Marcos R. O. A. Máximo:
Multiagent Reinforcement Learning for Strategic Decision Making and Control in Robotic Soccer Through Self-Play. IEEE Access 10: 72628-72642 (2022) - [j7]Angelo Caregnato-Neto, Marcos Ricardo Omena de Albuquerque Máximo, Rubens Junqueira Magalhães Afonso:
A line of sight constraint based on intermediary points for connectivity maintenance of multiagent systems using mixed-Integer programming. Eur. J. Control 68: 100671 (2022) - [j6]Alexandre F. V. Muzio, Marcos Ricardo Omena de Albuquerque Máximo, Takashi Yoneyama:
Deep Reinforcement Learning for Humanoid Robot Behaviors. J. Intell. Robotic Syst. 105(1): 12 (2022) - [j5]Dicksiano Carvalho Melo, Marcos Ricardo Omena de Albuquerque Máximo, Adilson Marques da Cunha:
Learning Push Recovery Behaviors for Humanoid Walking Using Deep Reinforcement Learning. J. Intell. Robotic Syst. 106(1): 8 (2022) - [c34]Francisco A. B. Azevedo, Guilherme P. C. Leão, Marcos R. O. de A. Máximo:
Deep Neural Network Algorithm to Control a Curved Kicking Mechanism in RoboCup Small Size League. LARS/SBR/WRE 2022: 1-6 - [c33]André O. Françani, Marcos R. O. de A. Máximo:
Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometry. LARS/SBR/WRE 2022: 1-6 - [c32]Guilherme Corrêa de Freitas, Marcos R. O. de A. Máximo, Filipe Alves Neto Verri:
Semi-Supervised Learning for Intelligent Surveillance. LARS/SBR/WRE 2022: 1-6 - [c31]Luiz Giacomossi, Angelo Caregnato-Neto, Marcos R. O. de A. Máximo:
Optimization of Force and Torque Bounds for the Flight Control System of a Quadcopter using PSO. LARS/SBR/WRE 2022: 1-6 - [c30]Gabriel de Almeida Souza, Octávio Mathias Silva, Marcos R. O. de A. Máximo:
Thrust Vectored Rocket Landing Integrated Guidance and Control with Proximal Policy Optimization. LARS/SBR/WRE 2022: 1-6 - [c29]Guilherme T. T. Bernardo, Luan Mateus Bocalan Vogás, Sargon D. S. Rodrigues, Thiago G. G. Lopes, Cesar Augusto Cavalheiro Marcondes, Denis Silva Loubach, Elton Felipe Sbruzzi, Filipe Alves Neto Verri, Johnny Cardoso Marques, Lourenço Alves Pereira Júnior, Marcos R. O. de A. Máximo, Vitor Venceslau Curtis:
A-Star Based Algorithm Applied to Target Search and Rescue by a UAV Swarm. LARS/SBR/WRE 2022: 49-54 - [c28]Guilherme Reis Miguel, Marcos R. O. de A. Máximo, Izabela Batista Henriques:
Thermal Modeling of Electric Motors Used in Very Small Size Soccer Robots. LARS/SBR/WRE 2022: 270-275 - [c27]Leonardo Silveira, Mateus Rodrigues, Bruno S. Faiçal, Alexandre S. Quirino da Silva, Cesar Marcondes, Marcos R. O. de A. Máximo, Filipe Alves Neto Verri:
Navigation Aids Based on Optical Flow and Convolutional Neural Network. LARS/SBR/WRE 2022: 318-323 - [c26]Lucas Steuernagel, Marcos Ricardo Omena de Albuquerque Máximo:
Trajectory Prediction for SSL Robots Using Seq2seq Neural Networks. RoboCup 2022: 27-38 - [c25]Guilherme N. Oliveira, Marcos Ricardo Omena de Albuquerque Máximo, Vitor Venceslau Curtis:
Distributed Optimization Tool for RoboCup 3D Soccer Simulation League Using Intel DevCloud. RoboCup 2022: 152-163 - [c24]Joao P. A. Dantas, Andre N. Costa, Felipe L. L. Medeiros, Diego Geraldo, Marcos R. O. A. Máximo, Takashi Yoneyama:
Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations. WSC 2022: 1990-2001 - [i10]Joao P. A. Dantas, Andre N. Costa, Marcos R. O. A. Máximo, Takashi Yoneyama:
Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem. CoRR abs/2201.07208 (2022) - [i9]Rafael Figueiredo Prudencio, Marcos R. O. A. Máximo, Esther Luna Colombini:
A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems. CoRR abs/2203.01387 (2022) - [i8]Angelo Caregnato-Neto, Marcos Ricardo Omena de Albuquerque Máximo, Rubens Junqueira Magalhães Afonso:
Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming. CoRR abs/2206.00097 (2022) - [i7]Joao P. A. Dantas, Andre N. Costa, Felipe L. L. Medeiros, Diego Geraldo, Marcos R. O. A. Máximo, Takashi Yoneyama:
Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations. CoRR abs/2207.04188 (2022) - [i6]André O. Françani, Marcos R. O. A. Máximo:
Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometry. CoRR abs/2210.01723 (2022) - 2021
- [j4]Luckeciano Carvalho Melo, Dicksiano Carvalho Melo, Marcos Ricardo Omena de Albuquerque Máximo:
Learning Humanoid Robot Running Motions with Symmetry Incentive through Proximal Policy Optimization. J. Intell. Robotic Syst. 102(3): 54 (2021) - [c23]Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos Ricardo Omena Albuquerque Máximo, Takashi Yoneyama:
Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep Neural Network. BRACIS (2) 2021: 193-207 - [c22]Luiz Giacomossi, Flavio Souza, Raphael Gomes Cortes, Huascar Mirko Montecinos Cortez, Caue Ferreira, Cesar Augusto Cavalheiro Marcondes, Denis Silva Loubach, Elton Felipe Sbruzzi, Filipe Alves Neto Verri, Johnny Cardoso Marques, Lourenço Alves Pereira Jr., Marcos R. O. A. Máximo, Vitor Venceslau Curtis:
Autonomous and Collective Intelligence for UAV Swarm in Target Search Scenario. LARS/SBR/WRE 2021: 72-77 - [c21]Luiz Giacomossi, Stiven Schwanz Dias, José Fernando Basso Brancalion, Marcos R. O. A. Máximo:
Cooperative and Decentralized Decision-Making for Loyal Wingman UAVs. LARS/SBR/WRE 2021: 78-83 - [c20]Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos R. O. A. Máximo, Takashi Yoneyama:
Engagement Decision Support for Beyond Visual Range Air Combat. LARS/SBR/WRE 2021: 96-101 - [c19]Débora F. Dos Santos, André O. Françani, Marcos R. O. A. Máximo, Arthur S. C. Ferreira:
Performance Comparison of Convolutional Neural Network Models for Object Detection in Tethered Balloon Imagery. LARS/SBR/WRE 2021: 246-251 - [c18]Gustavo L. Silva, Marcos R. O. A. Máximo, Lourenço Alves Pereira Jr.:
A Minimalist Open Source Behavior Tree Framework in C++. LARS/SBR/WRE 2021: 306-311 - [c17]Thayna Pires Baldão, Marcos R. O. A. Máximo, Takashi Yoneyama:
Optimizing Univector Field Navigation Parameters Using CMA-ES. LARS/SBR/WRE 2021: 318-323 - [i5]Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos R. O. A. Máximo, Takashi Yoneyama:
Engagement Decision Support for Beyond Visual Range Air Combat. CoRR abs/2111.03059 (2021) - [i4]Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos R. O. A. Máximo, Takashi Yoneyama:
Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep Neural Network. CoRR abs/2111.04474 (2021) - 2020
- [j3]Filipe Alves Neto Verri, Cesar Augusto Cavalheiro Marcondes, Denis Silva Loubach, Elton Felipe Sbruzzi, Johnny Cardoso Marques, Lourenço Alves Pereira Júnior, Marcos Ricardo Omena de Albuquerque Máximo, Vitor Venceslau Curtis:
An Analysis on Tradable Permit Models for Last-Mile Delivery Drones. IEEE Access 8: 186279-186290 (2020) - [j2]Guilherme C. G. Fernandes, Stiven S. Dias, Marcos R. O. A. Máximo, Marcelo G. S. Bruno:
Cooperative Localization for Multiple Soccer Agents Using Factor Graphs and Sequential Monte Carlo. IEEE Access 8: 213168-213184 (2020) - [j1]Marcos R. O. A. Máximo, Carlos H. C. Ribeiro, Rubens Junqueira Magalhães Afonso:
Real-time walking step timing adaptation by restricting duration decision for the first footstep. Adv. Robotics 34(21-22): 1420-1441 (2020) - [c16]Francisco A. B. Azevedo, Daniela Vacarini, Emília Villani, Marcos R. O. A. Máximo:
Neural Network to Control a Multiple Angles Kicker in RoboCup Small Size League. LARS/SBR/WRE 2020: 1-6 - [c15]Thayna Pires Baldão, Marcos R. O. A. Máximo, Cecília de Azevedo Castro César:
Decision-making for 5×5 Very Small Size Soccer Teams. LARS/SBR/WRE 2020: 1-6 - [c14]Thiago Filipe de Medeiros, Marcos R. O. de A. Máximo, Takashi Yoneyama:
Deep Reinforcement Learning Applied to IEEE Very Small Size Soccer Strategy**This work was supported by ITAndroids' sponsors: Altium Cenic, Intel, ITAEx, MathWorks, Metinjo, Micropress, Polimold, Rapid, SolidWorks, STMicroelectronics, Wildlife Studios and Vir-tual. PYXIS. Also, Thiago Filipe de Medeiros would like to thank Capes for the master's scholarship grant 88882.446989/2019-01 and Takashi Yoneyama would like to thank CNPq - National Research Council of Brazil for the grant 304134/2018-0. LARS/SBR/WRE 2020: 1-6 - [c13]Dicksiano Carvalho Melo, Marcos Ricardo Omena Albuquerque Máximo, Adilson Marques da Cunha:
Push Recovery Strategies through Deep Reinforcement Learning. LARS/SBR/WRE 2020: 1-6 - [c12]Alexandre F. V. Muzio, Marcos R. O. A. Máximo, Takashi Yoneyama:
Deep Reinforcement Learning for Humanoid Robot Dribbling**Alexandre Muzio acknowledges CAPES for his scholarship (number 88882.161989/2017-01). Takashi Yoneyama would like to thank CNPq - National Research Council of Brasil for the grant 304134/2-18-0. The authors thank ITAndroids' sponsors: Altium, Cenic, Intel, ITAEx, MathWorks, Metinjo, Micropress, Polimold, Rapid, SolidWorks, STMicroelectronics, Wildlife Studios, and Virtual.PYXIS. LARS/SBR/WRE 2020: 1-6 - [c11]Felipe C. R. Pinheiro, Marcos R. O. A. Máximo, Takashi Yoneyama:
Comparison of Sampling-based Path Planners for Robocup Small Size League. LARS/SBR/WRE 2020: 1-6 - [c10]Lucas Steuernagel, Marcos R. O. A. Máximo, Lucas A. Pereira, Carlos A. A. Sanches:
Convolutional Neural Network with Inception-like Module for Ball and Goalpost Detection in a Small Humanoid Soccer Robot. LARS/SBR/WRE 2020: 1-6
2010 – 2019
- 2019
- [c9]Felipe Celso Reis Pinheiro, Marcos Ricardo Omena de Albuquerque Máximo, Takashi Yoneyama:
Model Predictive Control for Omnidirectional Small Size Robot with Motor and Non-Slipping Constraints. LARS/SBR/WRE 2019: 13-18 - [c8]Luckeciano Carvalho Melo, Marcos Ricardo Omena Albuquerque Máximo:
Learning Humanoid Robot Running Skills through Proximal Policy Optimization. LARS/SBR/WRE 2019: 37-42 - [c7]Dicksiano Carvalho Melo, Carlos Henrique Quartucci Forster, Marcos Ricardo Omena de Albuquerque Máximo:
Learning When to Kick through Deep Neural Networks. LARS/SBR/WRE 2019: 43-48 - [c6]Caroline C. D. Silva, Marcos R. O. A. Máximo, Luiz C. S. Góes:
Height Varying Humanoid Robot Walking through Model Predictive Control. LARS/SBR/WRE 2019: 49-54 - [i3]Luckeciano Carvalho Melo, Marcos Ricardo Omena Albuquerque Máximo, Adilson Marques da Cunha:
Learning Humanoid Robot Motions Through Deep Neural Networks. CoRR abs/1901.00270 (2019) - [i2]Luckeciano Carvalho Melo, Marcos Ricardo Omena Albuquerque Máximo, Adilson Marques da Cunha:
Bottom-Up Meta-Policy Search. CoRR abs/1910.10232 (2019) - [i1]Luckeciano Carvalho Melo, Marcos R. O. A. Máximo:
Learning Humanoid Robot Running Skills through Proximal Policy Optimization. CoRR abs/1910.10620 (2019) - 2017
- [c5]Bernardo P. Veronese, Igor F. Okuyama, Felipe C. R. Pinheiro, Marcos R. O. A. Máximo, Luis C. S. Goes:
Experimental measurement of parameters for modeling a differentia drive soccer robot. LARS/SBR 2017: 1-6 - 2016
- [c4]Marcos R. O. A. Máximo, Carlos H. C. Ribeiro, Rubens Junqueira Magalhães Afonso:
Mixed-integer programming for automatic walking step duration. IROS 2016: 5399-5404 - [c3]Francisco Muniz, Marcos Ricardo Omena Albuquerque Máximo, Carlos H. C. Ribeiro:
Keyframe Movement Optimization for Simulated Humanoid Robot Using a Parallel Optimization Framework. LARS/SBR 2016: 79-84 - [c2]Felipe Celso Reis Pinheiro, Samuel C. Pinto, Igor F. Okuyama, Marcos R. O. A. Máximo, Natan L. Viana:
Performance Requirements Derivation for IEEE Very Small Size Competition. LARS/SBR 2016: 109-114 - [c1]Alexandre F. V. Muzio, Luis Aguiar, Marcos Ricardo Omena Albuquerque Máximo, Samuel C. Pinto:
Monte Carlo Localization with Field Lines Observations for Simulated Humanoid Robotic Soccer. LARS/SBR 2016: 334-339
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:06 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
