Schlagworte:
- 3D-color-grayscale conversion
- Alzheimer disease
- Alzheimer's disease
- artificial intelligence
- Automatic weak labels
- Biological signal acquisition
- BLS
- Chopped carbon fiber
- Classification
- Clinical decision support
- clustering
- contrastive learning
- Deep convolutional neural network
- Deep Learning
- digital pathology
- EEG
- Electromagnetic interference shielding
- Explainable AI
- Flexible sensor
- Histopathology
- Histopathology image classification
- image retrieval
- interpretability
- Longitudinal clustering
- machine learning
- MOT
- Natural Language Processing
- NIHSS
- Noisy labels
- Open access
- Parkinson's disease
- pathology classification
- Recovery ratio
- retrospective matching network
- Scanning electron microscopy
- self-supervised learning
- SEMG
- ShallowNet
- Stroke
- transformer
- UAV
- whole slide imaging
Publikationen von Manfredo Atzori sortiert nach Titel
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| , , und , Kinematic synergies of hand grasps: a comprehensive study on a large publicly available dataset (2019), in: Journal of Neuroengineering and rehabilitation |
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| , , , , und , Live ECG Readings Using Google Glass in Emergency Situations, in: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano, Italy, 2015 |
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| , , und , Mapping of the Upper Limb Work-Space: Benchmarking Four Wrist Smoothness Metrics (2022), in: Applied Sciences, 12:24(12643) |
, , , und , Measuring Movement Classification Performance with the Movement Error Rate (2014), in: IEEE Transactions on neural systems and rehabiliation engineering
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| , , , , , , , , , , , und , Megane Pro: myo-electricity, visual and gaze tracking integration as a resource for dexterous hand prosthetics, in: IEEE International Conference on Rehabilitation Robotics, London, UK, 2017 |
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| , , , , , , , , , und , Modelling digital health data: The ExaMode ontology for computational pathology (2023), in: Journal of Pathology Informatics(100332) |
| , , , , , , , , , , , und , Modelling digital health data: The ExaMode ontology for computational pathology (2023), in: PMC |
[DOI] |
| , , , , , , , , und , Multi-functional control and usage of a 3D printed robotic hand prosthesis with the Myo armband by hand amputees (2018), in: BioRxiv |
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| , , , , , , , und , Multi-Scale Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations, in: COMPAY workshop at MICCAI, 2021 |
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| , , , , , , , , , , , und , Multimodal Representations of Biomedical Knowledge from Limited Training Whole Slide Images and Reports using Deep Learning (2024), in: Medical Image Analysis |
[DOI] |
| , , , , , , , , , und , Multimodal Schizophrenia Detection by Multiclassification Analysis, in: Proceedings of the Iberoamerican Congress on Pattern Recognition 2011, Pucón, Chile, Seiten 491-498, 2011 |
| , , , , , , und , Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images (2021), in: Frontiers in Computer Science |
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| , , , und , Muscle Synergy Analysis of a Hand-Grasp Dataset: a limited subset of motor modules may underlie a large variety of grasps (2018), in: Frontiers in Neurorobotics |
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| , , , , , , und , Myo electricity and 3D printing: a resource for revolutionary hand prosthetics, in: FESSH, Berlin, Germany, 2019 |
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| , , , , , , , und , Myo electricity and 3D printing: a resource for revolutionary hand prosthetics, in: FESSH, Berlin (Germany), 2019 |
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| , , , , , , , , , , , , und , Myo-electricity and gaze tracking data to improve hand prosthetics and neuro-cognitive examination, in: FESSH 2018, Copenhagen, Denmark, 2018 |
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| , , und , Natural Control Capabilities of Robotic Hands by Hand Amputated Subjects, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago (USA), IEEE, 2014 |
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| und , NINAPRO Project First Milestone: Set Up of the Data Base, institute of Business Information Systems, University of Applied Sciences Western Switzerland, Sierre (HES-SO Valais), 2012 |
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| , NMR Scans of the Brain: an Automatic Analysis Algorithm Based on the Features of the Tissues, University of Padova, Department of Physics, 2006 |
| , , , , , und , Nuove frontiere in Bio-robotica: Acquisizioni di Segnali Tramite Elettromiografia di Superficie per il Riconoscimento di Movimenti della Mano, in: Congresson Nazionale della Società Italiana di Chirurgia della Mano, Rimini, Italy, 2013 |
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| , , , , , , und , Obstacles to mental imagery: How bodily constraints affect apparent motion perception of human body parts. A proposed experiment., in: International Brain-Computer Interface (BCI) Meeting, Darmstadt, 2016 |
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, , , , und , On the visiomotor behavior of amputees and able-bodied people during grasping, (2019), in: Frontiers in Bioengienering and Biotechnology
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und , Parallel feature extraction tools to speed up feature extraction (2019), in: Frontiers in Neurorobotics
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| , , , und , Quantitative hierarchical representation and comparison of hand grasps from electromyography and kinematic data, in: Workshop Learning Applications for Intelligent Autonomous Robots, 15th International Conference on Intelligent Autonomous Systems, Baden-Baden, Germany, 2018 |
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| , , , , und , Questioning Domain Adaptation in Myoelectric Hand Prostheses Control: An Inter-and Intra-Subject Study (2021), in: Sensors, 21:22(7500) |
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| , und , Recognition of Hand Movements in a Trans–Radial Amputated Subject by sEMG, in: International Conference On Rehabilitation Robotics (ICORR) 2013, Seatlle, WA, USA, 2013 |
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| , , und , RegWSI: Whole slide image registration using combined deep feature- and intensity-based methods: Winner of the ACROBAT 2023 challenge (2024), in: Computer Methods and Programs in Biomedicine |
[DOI] |
| , , , , und , Retrospective Matching Network-Based One-Shot Multi-Object Tracking Method for UAV (2026), in: CONCURRENCY AND COMPUTATION, 38:1 |
[DOI] |
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| , , , , , , , und , Schizophrenia classification using regions of interest in brain MRI, in: Workshop in Intelligent Data Analysis in Biomedicine and Pharmacology, IDAMAP, Verona, Italy, 2009 |
| , , , , und , Self-Supervised Representation Learning for EEG-Based Detection of Neurodegenerative Diseases (2025), in: APPLIED SCIENCES, 15:24(13275--13275) |
[DOI] |
| , und , Semantic wikis as flexible database interfaces for biomedical applications (2023), in: Scientific Reports, 13:1(1095) |
| , , , , , , , und , Semi-automatic training of an object recognition system in scene camera data using gaze tracking and accelerometers, in: International Conference on Computer Vision Systems (ICVS), Shenzhen (China), 2017 |
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| , , und , Semi-supervised learning with a teacher-student paradigm for histopathology classification: a resource to face data heterogeneity and lack of local annotations, in: Workshop Artificial Intelligence for Digital Pathology, ICPR, Milano, Italy, 2021 |
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| , , und , Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: an experiment on histopathology image classification (2021), in: Medical Image Analysis |
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| , , und , Semi-Weakly Supervised Learning for Prostate Cancer Image Classification with Teacher-Student Deep Convolutional Networks, in: MICCAI workshop Labels, Lima, Peru, 2020 |
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| , , , und , Spatial and temporal muscle synergies provide a dual characterization of low-dimensional and intermittent control of upper-limb movements (2023), in: Neuroscience, 514(100--122) |
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| , und , Spatial Registration of Hand Muscle Electromyography Signals, in: 7th International Workshop on Biosignal Interpretation, Como, Italy, 2012 |
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, , , und , Staining invariant features for improving generalization of deep convolutional neural networks in computational pathology (2019), in: Frontiers in Bioengineering and Biotechnology-Bioinformatics and Computational Biology
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| , , , , , , und , stainlib: a python library for augmentation and normalization of histopathology H&E images (2022), in: bioArXiv |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue (2024), in: Medical Image Analysis |
[DOI] |
| , , , und , The more, the better? Evaluating the role of EEG preprocessing for deep learning applications. (2025), in: IEEE Transactions on Neural Systems and Rehabilitation Engineering |
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| und , The Ninapro database: a Resource for sEMG Naturally Controlled Robotic Hand Prosthetics, in: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano, Italy, 2015 |
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| , , , , und , The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: a preliminary study (2025), in: Computers in Biology and Medicine, 196(110608) |
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| , , und , TokenUNet: A new case for transformers integration in efficient and interpretable 3D UNets for brain imaging segmentation (2026), in: PloS one, 21:8(e0354511) |
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| und , Toward improving reproducibility in neuroimaging deep learning studies (2024), in: Frontiers in Neuroscience, 18(1509358) |
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| , , , , und , Training a deep neural network for small and highly heterogeneous MRID datasets for cancer grading, in: EMBC Conference, IEEE, 2020 |
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| , , , , und , Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading, in: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC), IEEE, Seiten 1758--1761, 2020 |
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| , , , , , , , , und , TransformEEG: Towards Improving Model Generalizability in Deep Learning-based EEG Parkinson's Disease Detection (2025), in: arXiv preprint arXiv:2507.07622 |
| , , , , , , , , und , TransformEEG: Towards improving model generalizability in deep learning-based EEG Parkinson’s disease detection (2025), in: Elsevier |
[DOI] |