Literatura científica selecionada sobre o tema "AI-based compression"
Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos
Consulte a lista de atuais artigos, livros, teses, anais de congressos e outras fontes científicas relevantes para o tema "AI-based compression".
Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.
Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.
Artigos de revistas sobre o assunto "AI-based compression"
Sarinova, Assiya, e Alexander Zamyatin. "Methodology for Developing Algorithms for Compressing Hyperspectral Aerospace Images used on Board Spacecraft". E3S Web of Conferences 223 (2020): 02007. http://dx.doi.org/10.1051/e3sconf/202022302007.
Texto completo da fonteSarinova, Assiya. "Development of compression algorithms for hyperspectral aerospace images based on discrete orthogonal transformations". E3S Web of Conferences 333 (2021): 01011. http://dx.doi.org/10.1051/e3sconf/202133301011.
Texto completo da fonteKim, Myung-Jun, e Yung-Lyul Lee. "Object Detection-Based Video Compression". Applied Sciences 12, n.º 9 (29 de abril de 2022): 4525. http://dx.doi.org/10.3390/app12094525.
Texto completo da fontePinheiro, Antonio. "JPEG column: 89th JPEG meeting". ACM SIGMultimedia Records 12, n.º 4 (dezembro de 2020): 1. http://dx.doi.org/10.1145/3548580.3548583.
Texto completo da fonteSarinova, Assiya, Pavel Dunayev, Aigul Bekbayeva, Ali Mekhtiyev e Yermek Sarsikeyev. "Development of compression algorithms for hyperspectral aerospace images based on discrete orthogonal transformations". Eastern-European Journal of Enterprise Technologies 1, n.º 2(115) (25 de fevereiro de 2022): 22–30. http://dx.doi.org/10.15587/1729-4061.2022.251404.
Texto completo da fonteNagarsenker, Anish, Prasad Khandekar e Minal Deshmukh. "JPEG2000-Based Semantic Image Compression using CNN". International journal of electrical and computer engineering systems 14, n.º 5 (5 de junho de 2023): 527–34. http://dx.doi.org/10.32985/ijeces.14.5.4.
Texto completo da fontePetraikin, A. V., Zh E. Belaya, A. N. Kiseleva, Z. R. Artyukova, M. G. Belyaev, V. A. Kondratenko, M. E. Pisov et al. "Artificial intelligence for diagnosis of vertebral compression fractures using a morphometric analysis model, based on convolutional neural networks". Problems of Endocrinology 66, n.º 5 (25 de dezembro de 2020): 48–60. http://dx.doi.org/10.14341/probl12605.
Texto completo da fonteJane, Robert, Tae Young Kim, Samantha Rose, Emily Glass, Emilee Mossman e Corey James. "Developing AI/ML Based Predictive Capabilities for a Compression Ignition Engine Using Pseudo Dynamometer Data". Energies 15, n.º 21 (28 de outubro de 2022): 8035. http://dx.doi.org/10.3390/en15218035.
Texto completo da fonteMa, Xiaoqian. "Analysis on the Application of Multimedia-Assisted Music Teaching Based on AI Technology". Advances in Multimedia 2021 (27 de dezembro de 2021): 1–12. http://dx.doi.org/10.1155/2021/5728595.
Texto completo da fonteBai, Ye, Fei Bo, Wencan Ma, Hongwei Xu e Dawei Liu. "Effect of Interventional Therapy on Iliac Venous Compression Syndrome Evaluated and Diagnosed by Artificial Intelligence Algorithm-Based Ultrasound Images". Journal of Healthcare Engineering 2021 (22 de julho de 2021): 1–8. http://dx.doi.org/10.1155/2021/5755671.
Texto completo da fonteTeses / dissertações sobre o assunto "AI-based compression"
Berthet, Alexandre. "Deep learning methods and advancements in digital image forensics". Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS252.
Texto completo da fonteThe volume of digital visual data is increasing dramatically year after year. At the same time, image editing has become easier and more precise. Malicious modifications are therefore more accessible. Image forensics provides solutions to ensure the authenticity of digital visual data. Recognition of the source camera and detection of falsified images are among the main tasks. At first, the solutions were classical methods based on the artifacts produced during the creation of a digital image. Then, as in other areas of image processing, the methods moved to deep learning. First, we present a state-of-the-art survey of deep learning methods for image forensics. Our state-of-the-art survey highlights the need to apply pre-processing modules to extract artifacts hidden by image content. We also highlight the problems concerning image recognition evaluation protocols. Furthermore, we address counter-forensics and present compression based on artificial intelligence, which could be considered as an attack. In a second step, this thesis details three progressive evaluation protocols that address camera recognition problems. The final protocol, which is more reliable and reproducible, highlights the impossibility of state-of-the-art methods to recognize cameras in a challenging context. In a third step, we study the impact of compression based on artificial intelligence on two tasks analyzing compression artifacts: tamper detection and social network recognition. The performances obtained show on the one hand that this compression must be taken into account as an attack, but that it leads to a more important decrease than other manipulations for an equivalent image degradation
Desai, Ujjaval Y., Marcelo M. Mizuki, Ichiro Masaki e Berthold K. P. Horn. "Edge and Mean Based Image Compression". 1996. http://hdl.handle.net/1721.1/5943.
Texto completo da fonteCapítulos de livros sobre o assunto "AI-based compression"
Li, Ge, Wei Gao e Wen Gao. "MPEG AI-Based 3D Graphics Coding Standard". In Point Cloud Compression, 219–41. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1957-0_10.
Texto completo da fonteFalk, Eric. "AI to Solve the Data Deluge: AI-Based Data Compression". In Future of Business and Finance, 271–85. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41309-5_18.
Texto completo da fonteBecking, Daniel, Maximilian Dreyer, Wojciech Samek, Karsten Müller e Sebastian Lapuschkin. "ECQ$$^{\text {x}}$$: Explainability-Driven Quantization for Low-Bit and Sparse DNNs". In xxAI - Beyond Explainable AI, 271–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04083-2_14.
Texto completo da fonteOni-Orisan, Oluwatomiwa. "Viability of Knowledge Management Practices for a Successful Digital Transformation in Small- and Medium- Sized Enterprises". In Informatik aktuell, 129–39. Wiesbaden: Springer Fachmedien Wiesbaden, 2024. http://dx.doi.org/10.1007/978-3-658-43705-3_10.
Texto completo da fonteSandhya, Mandha, e G. Mallikarjuna Rao. "Prediction of Compressive Strength of Fly Ash-Based Geopolymer Concrete Using AI Approach". In Lecture Notes in Civil Engineering, 9–20. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8496-8_2.
Texto completo da fonteDayal, Sankalp. "AI on Edge: A Mass Accessible Tool for Decision Support Systems". In Decision Support Systems (DSS) and Tools [Working Title]. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1003945.
Texto completo da fonteOommen, B. John, e Luis Rueda. "Stochastic Learning-based Weak Estimation and Its Applications". In Knowledge-Based Intelligent System Advancements, 1–29. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-61692-811-7.ch001.
Texto completo da fonteChakraborty, Sanjay, e Lopamudra Dey. "Image Representation, Filtering, and Natural Computing in a Multivalued Quantum System". In Handbook of Research on Natural Computing for Optimization Problems, 689–717. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0058-2.ch028.
Texto completo da fonteFratrič, Peter, Giovanni Sileno, Tom van Engers e Sander Klous. "A Compression and Simulation-Based Approach to Fraud Discovery". In Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia220463.
Texto completo da fonteTrabalhos de conferências sobre o assunto "AI-based compression"
Bergmann, Sandra, Denise Moussa, Fabian Brand, André Kaup e Christian Riess. "Frequency-Domain Analysis of Traces for the Detection of AI-based Compression". In 2023 11th International Workshop on Biometrics and Forensics (IWBF). IEEE, 2023. http://dx.doi.org/10.1109/iwbf57495.2023.10157489.
Texto completo da fonteStroot, Markus, Stefan Seiler, Philipp Lutat e Andreas Ulbig. "Comparative Analysis of Modern, AI-based Data Compression on Power Quality Disturbance Data". In 2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). IEEE, 2023. http://dx.doi.org/10.1109/smartgridcomm57358.2023.10333901.
Texto completo da fonteBerthet, Alexandre, Chiara Galdi e Jean-Luc Dugelay. "On the Impact of AI-Based Compression on Deep Learning-Based Source Social Network Identification". In 2023 IEEE 25th International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2023. http://dx.doi.org/10.1109/mmsp59012.2023.10337726.
Texto completo da fonteBerthet, Alexandre, e Jean-Luc Dugelay. "AI-Based Compression: A New Unintended Counter Attack on JPEG-Related Image Forensic Detectors?" In 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2022. http://dx.doi.org/10.1109/icip46576.2022.9897697.
Texto completo da fonteJane, Robert, Corey James, Samantha Rose e Tae Kim. "Developing Artificial Intelligence (AI) and Machine Learning (ML) Based Soft Sensors for In-Cylinder Predictions with a Real-Time Simulator and a Crank Angle Resolved Engine Model". In WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0102.
Texto completo da fonteMisra, Siddharth, Jungang Chen, Polina Churilova e Yusuf Falola. "Generative Artificial Intelligence for Geomodeling". In International Petroleum Technology Conference. IPTC, 2024. http://dx.doi.org/10.2523/iptc-23477-ms.
Texto completo da fonteMa, jialin, hang hu e Yuetong Zhang. "Reconfigurable pulse-compression signal generation based on DP-QPSK modulator". In AI in Optics and Photonics, editado por Juejun Hu e Jianji Dong. SPIE, 2023. http://dx.doi.org/10.1117/12.3007024.
Texto completo da fonteKang, Haoyan, Jiachi Ye, Behrouz Movahhed Nouri, Belal Jahannia, Salem Altaleb, Hao Wang, Elham Heidari, Volker Sorger e Hamed Dalir. "Reconfigurable complex convolution module based optical data compression and hashing algorithm". In AI and Optical Data Sciences V, editado por Volker J. Sorger e Ken-ichi Kitayama. SPIE, 2024. http://dx.doi.org/10.1117/12.3003411.
Texto completo da fonteThambi, Joel Luther, Subhransu Sekhar Mohapatra, Vinod Jose Kavalakkat, Subhransu S. Mohapatra, Ullas U e Saibal Kanchan Barik. "A Combined Data Science and Simulation-Based Methodology for Efficient and Economic Prediction of Thermoplastic Performance for Automotive Industry". In WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0936.
Texto completo da fonteAkita, Eiji, Shin Gomi, Scott Cloyd, Michael Nakhamkin e Madhukar Chiruvolu. "The Air Injection Power Augmentation Technology Provides Additional Significant Operational Benefits". In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-28336.
Texto completo da fonte