Suchergebnisse - ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.0: Deterministic~

Landscape metrics as indicator for ecological significance: assessment of Sitno Natura 2000 sites, Slovakia

Autoren: Klaučo, Michal Gregorová, Bohuslava Stankov, Ugljesa et al.

Weitere Verfasser: Klaučo, Michal Gregorová, Bohuslava Stankov, Ugljesa et al.

Quelle: Ecology and Environmental Protection ; https://hal.archives-ouvertes.fr/hal-01972864 ; Ecology and Environmental Protection, Belarusian State University, Mar 2014, Minsk, Belarus. pp.85-90, ⟨10.6084/m9.figshare.7434200⟩ ; http://elib.bsu.by/handle/123456789/103362

Schlagwörter: Landscape Analysis, Landscape Ecology, NATURA 2000, Environment, Environmental assessment, Land Cover Mapping, Land Cover Type, Landscape Dynamic, Slovak Republic, Geoinformatics, Geoinformation, Mapping, GIS Analysis, GIS & Spatial Analyses, Landscape Pattern, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.5: Structural, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.0: Deterministic, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering/I.5.3.0: Algorithms, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering/I.5.3.1: Similarity measures, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING/I.6.5: Model Development/I.6.5.0: Modeling methodologies, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING/I.6.7: Simulation Support Systems/I.6.7.0: Environments, ACM: I.: Computing Methodologies, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDE.ES]Environmental Sciences/Environmental and Society, [SDE.MCG]Environmental Sciences/Global Changes, [SDE.IE]Environmental Sciences/Environmental Engineering

Geographisches Schlagwort: Minsk, Belarus

Relation: hal-01972864; https://hal.archives-ouvertes.fr/hal-01972864; https://hal.archives-ouvertes.fr/hal-01972864/document; https://hal.archives-ouvertes.fr/hal-01972864/file/Klauco_etal_2014_LANDSCAPE%20METRICS_Minsk_BGU_85-90.pdf

Verfügbarkeit: https://hal.archives-ouvertes.fr/hal-01972864
https://hal.archives-ouvertes.fr/hal-01972864/document
https://hal.archives-ouvertes.fr/hal-01972864/file/Klauco_etal_2014_LANDSCAPE%20METRICS_Minsk_BGU_85-90.pdf
https://doi.org/10.6084/m9.figshare.7434200

The inherent adversarial robustness of analog in-memory computing.

Autoren: Lammie, Corey Büchel, Julian Vasilopoulos, Athanasios et al.

Quelle: Nature Communications; 2/18/2025, Vol. 16 Issue 1, p1-12, 12p

Schlagwörter: ARTIFICIAL neural networks, TRANSFORMER models, PHASE change memory, ARTIFICIAL intelligence, IMAGE recognition (Computer vision)

A FIRST STAGE COMPARATIVE SURVEY ON HUMAN ACTIVITY RECOGNITION METHODOLOGIES.

Autoren: TSITSOULIS, ATHANASIOS BOURBAKIS, NIKOLAOS

Quelle: International Journal on Artificial Intelligence Tools; Dec2013, Vol. 22 Issue 6, p-1, 51p

Schlagwörter: COMPARATIVE studies, HUMAN activity recognition, SCIENTIFIC community, ARTIFICIAL intelligence, STREAMING video & television, IMAGE processing

Efficient Deep Learning Infrastructures for Embedded Computing Systems: A Comprehensive Survey and Future Envision.

Autoren: Luo, Xiangzhong Liu, Di Kong, Hao et al.

Quelle: ACM Transactions on Embedded Computing Systems; Jan2025, Vol. 24 Issue 1, p1-100, 100p

Schlagwörter: ARTIFICIAL neural networks, LANGUAGE models, MACHINE learning, TRANSFORMER models, IMAGE recognition (Computer vision), DEEP learning

Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Survey.

Autoren: Liu, Zhihong Xu, Xin Qiao, Peng et al.

Quelle: ACM Computing Surveys; Apr2025, Vol. 57 Issue 4, p1-35, 35p

Schlagwörter: REINFORCEMENT learning, ARTIFICIAL neural networks, DEEP reinforcement learning, DISTRIBUTED artificial intelligence, PATTERN recognition systems, HETEROGENEOUS computing, PARALLEL algorithms

A Survey on Silicon Photonics for Deep Learning.

Autoren: SUNNY, FEBIN P. TAHERI, EBADOLLAH NIKDAST, MAHDI et al.

Quelle: ACM Journal on Emerging Technologies in Computing Systems; Oct2021, Vol. 17 Issue 4, p1-57, 57p

Schlagwörter: DEEP learning, ARTIFICIAL neural networks, NATURAL language processing, PATTERN recognition systems, APPLICATION-specific integrated circuits, COMPUTER vision

Combining Structure and Parameter Adaptation of HMMs for Printed Text Recognition

Autoren: Ait-Mohand, Kamel Paquet, Thierry Ragot, Nicolas et al.

Weitere Verfasser: Ait-Mohand, Kamel Paquet, Thierry Ragot, Nicolas et al.

Quelle: IEEE Transactions on Pattern Analysis and Machine Intelligence. 36:1716-1732

Schlagwörter: Optimization, Optical character recognition software, parameter adaptation, Character recognition, structure adaptation, historical documents, Data models, Adaptation models, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 02 engineering and technology, 16. Peace & justice, ACM: I.: Computing Methodologies/I.7: DOCUMENT AND TEXT PROCESSING/I.7.5: Document Capture/I.7.5.2: Optical character recognition (OCR), ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, 03 medical and health sciences, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology/I.5.2.0: Classifier design and evaluation, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], printed text recognition, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, 0202 electrical engineering, electronic engineering, information engineering, Training, Hidden Markov models, 0305 other medical science

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/26352227

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges.

Autoren: KLEYKO, DENIS RACHKOVSKIJ, DMITRI OSIPOV, EVGENY et al.

Quelle: ACM Computing Surveys; Sep2023, Vol. 55 Issue 9, p1-52, 52p

Schlagwörter: ARTIFICIAL intelligence, MACHINE learning, PERSONAL names, COGNITIVE computing, BLOCK codes, BINARY codes

Service Caching and Computation Reuse Strategies at the Edge: A Survey.

Autoren: BARRIOS, CARLOS KUMAR, MOHAN

Quelle: ACM Computing Surveys; Feb2024, Vol. 56 Issue 2, p1-38, 38p

Schlagwörter: EDGE computing, DEEP learning, ARTIFICIAL intelligence, ARTIFICIAL neural networks, REINFORCEMENT learning, DEEP reinforcement learning, PATTERN recognition systems

Making research methodologies in theoretical computing explicit.

Autoren: Sanders, Ian Pilkington, Colin Pretorius, Laurette

Quelle: South African Computer Journal; Jul2022, Vol. 34 Issue 1, p192-216, 25p

Schlagwörter: RESEARCH methodology, WORLDVIEW, CONCEPTUAL models, GRADUATE students, SCIENTIFIC method

A Review of Stability in Topic Modeling: Metrics for Assessing and Techniques for Improving Stability.

Autoren: Hosseiny Marani, Amin Baumer, Eric P. S.

Quelle: ACM Computing Surveys; May2024, Vol. 56 Issue 5, p1-32, 32p

Schlagwörter: MACHINE learning, AUTOMATIC speech recognition, ARTIFICIAL intelligence, NATURAL language processing, PATTERN recognition systems, DOCUMENT clustering, LATENT semantic analysis

A positive feedback method based on F-measure value for Salient Object Detection

Autoren: Pan, Ailing Dai, Chao Pan, Chen et al.

Schlagwörter: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, ACM-class: I.4 COMPUTING METHODOLOGIES, I.4.9 Image Processing and Computer Vision, I.5.4 Pattern Recognition

Zugangs-URL: http://arxiv.org/abs/2304.14619

SOFT COMPUTING PATTERN RECOGNITION, CASE GENERATION AND DATA MINING.

Autoren: PAL, SANKAR K.

Quelle: Active Media Technology - Proceedings of the Second International Conference; 2003, p34-45, 12p

Schlagwörter: SOFT computing, ARTIFICIAL intelligence, DATA mining, BIG data, MACHINE learning

105 Diffusion Models: A Comprehensive Survey of Methods and Applications.

Autoren: LING YANG ZHILONG ZHANG YANG SONG et al.

Quelle: ACM Computing Surveys; Apr2024, Vol. 56 Issue 4, p1-39, 39p

Schlagwörter: ARTIFICIAL neural networks, PATTERN recognition systems, JENSEN'S inequality, GRAPH neural networks, CONVOLUTIONAL neural networks, LATENT variables, IMAGE reconstruction algorithms, DEEP learning, TEXT recognition

Automatic Speech Recognition: Architecture, Methodologies and Challenges - A Review.

Autoren: Karpagavalli, S. Deepika, R. Kokila, P. et al.

Quelle: International Journal of Advanced Research in Computer Science; Nov/Dec2011, Vol. 2 Issue 6, p326-331, 6p

Schlagwörter: AUTOMATIC speech recognition, PERFORMANCE evaluation, SIGNAL processing, PATTERN recognition systems, SIGNAL theory

Generative AI in the Information Society: Implications for Higher Education and Research.

Autoren: Levin, Ilya Bukhshtaber, Natalia Minyar-Beloruchev, Konstantin

Quelle: BRAIN: Broad Research in Artificial Intelligence & Neuroscience; Feb2025, Vol. 16 Issue 1, p10-21, 12p

Schlagwörter: GENERATIVE artificial intelligence, LANGUAGE models, SCIENTIFIC method, PATTERN recognition systems, EDUCATIONAL planning

Probabilistic Complex Event Recognition: A Survey.

Autoren: ALEVIZOS, ELIAS SKARLATIDIS, ANASTASIOS ARTIKIS, ALEXANDER et al.

Quelle: ACM Computing Surveys; Sep2018, Vol. 50 Issue 5, p71:1-71:31, 31p, 1 Diagram, 5 Charts, 1 Graph

Schlagwörter: DATA analysis, PROBABILITY theory, UNCERTAINTY, SKEPTICISM, PETRI nets

A Fast Scalable Automaton-Matching Accelerator for Embedded Content Processors.

Autoren: KUO-KUN TSENG YUAN-CHENG LAI YING-DAR LIN et al.

Quelle: ACM Transactions on Embedded Computing Systems; Apr2009, Vol. 8 Issue 3, p19-19-30, 30p, 13 Diagrams, 3 Charts, 1 Graph

Schlagwörter: MATCHING theory, EMBEDDED computer systems, NETWORK processors, ALGORITHMS, CONTENT filters (Computer science), COMPUTER network security, PATTERN recognition systems, COMPUTER memory management

Structure-aware Meta-fusion for Image Super-resolution.

Autoren: HAOYU MA BINGCHEN GONG YIZHOU YU

Quelle: ACM Transactions on Multimedia Computing, Communications & Applications; Apr2022, Vol. 18 Issue 2, p278-302, 25p

Schlagwörter: HIGH resolution imaging, PERCEPTUAL illusions, IMAGE fusion

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformations.

Autoren: KLEYKO, DENIS RACHKOVSKIJ, DMITRI A. OSIPOV, EVGENY

Quelle: ACM Computing Surveys; Jul2023, Vol. 55 Issue 6, p1-40, 40p

Schlagwörter: ARTIFICIAL intelligence, BINARY codes, COGNITIVE science, TENSOR products, COMPUTER science, COGNITIVE computing