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 , Control Capabilities of Myoelectric Robotic Prostheses by Hand Amputees: A Scientific Research and Market Overview (2015), in: Frontiers in Systems Neuroscience, 9(162-165) |
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| , und , Controllo della Mano Robotica: Andiamo Verso una Rivoluzione della Protesica, in: Congresso Nazionale della Società Italiana di Chirurgia della Mano, Foggia, Italy, 2014 |
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| , , , , , , und , Convolutional neural networks for an automatic classification of prostate tissue slides with high-grade Gleason score, in: SPIE Medical Imaging, Seiten 101400O-101400O-9, 2017 |
[DOI] [URL] |
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| , Data variability as a challenge to improve classification and retrieval in digital pathology, in: MICCAI, Computational Pathology Workshop (COMPAY), Granada (Spain), 2018 |
| , , , und , Deep learning based retrieval system for gigapixel histopathology cases and open access literature (2018), in: BioArXiv |
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| , , , und , Deep learning based retrieval system for gigapixel histopathology cases and open access literature (2019), in: Pathology Informatics |
[DOI] |
, und , Deep learning with convolutional neural networks: a resource for the control of robotic prosthetic hands via electromyography (2016), in: Frontiers in Neurorobotics, 10(9)
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[DOI] [URL] |
, , und , Deep Multimodal Case-Based Retrieval for Large Histopathology Datasets, in: MICCAI 2017 workshop on Patch-based image analysis, Quebec City, Canada, 2017
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| , , , , und , Determining the scale of image patches using a deep learning approach, in: IEEE International Symposium on Biomedical Imaging (ISBI), Washington, DC, USA, 2018 |
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| , , und , Deterministic Automatic Segmentation in MRI, CT and CTA: A Robust Method Based on Anatomical Structures Modeling and Local Recursive Intensity Analysis, in: 17th Joint Annual Meeting ISMRM-ESMRMB Scientific Proceedings, ISMRM-ESMRMB, Honolulu, Hawai’i, U.S., Seiten 357, 2009 |
| , , , , und , Development of a Deep Convolutional Neural Network to Predict the Grading of Canine Meningiomas from MR images (2018), in: The veterinary journal, 235(90-92) |
| , , , und , Dexterous Control of Prosthetic Hands, in: ICAR 2013 Proceedings, Montevideo, Uruguay, 2013 |
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| , , , und , EEG-To-fMRI Cross-Modal Prediction via Hierarchical Temporal Attention Network: Toward Accessible Functional Neuroimaging (2026), in: Concurrency and Computation: Practice and Experience, 38:14(e70860) |
| , , , und , Effect of movement type on the classification of electromyography data for the control of dexterous prosthetic hands, in: Biorob, International Conference on Biomedical Robotics & Biomechatronics, New York City, NY, USA, 2020 |
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| , , , , , , , , und , Effects of hand amputation surgery procedures on phantom limb sensation, in: FESSH, Berlin, Germany, 2019 |
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| , , , , , , , , und , Effects of hand amputation surgery procedures on sEMG activity to control robotic hand prostheses, in: FESSH, Berlin, Germany, 2019 |
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| , , , , und , Effects of Prosthesis Use on the Capability to Control Myoelectric Robotic Prosthetic Hands, in: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano (Italy), 2015 |
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| , , , , , , , und , Electromyography data for non-invasive naturally controlled robotic hand prostheses (2014), in: Scientific Data, 1:140053 |
[DOI] [URL] |
| , , und , Electromyography for Hand Prosthetics Demo, in: XXVIII Conférence francophone sur l'Interaction Homme-Machine, Fribourg, Suisse, 2016 |
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| und , Electromyography Low Pass Filtering Effects on the Classification of Hand Movements in Amputated Subjects, in: SCIEI International Conference on Digital Signal Processing (ICDSP), Milano, Italy, 2014 |
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| und , Electromyography Low Pass Filtering Effects on the Classification of Hand Movements in Amputated Subjects (2014), 3:2(118-122) |
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| , , und , Elettromiografia, protesica e robotica in rapido progresso verso l'amputazione funzionale: i risultati del progetto Ninapro (2016), in: Rivista di Chirurgia della mano, 53:3 |
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| , , , , , , und , Elsevier book on Texture Analysis, Kapitel Analysis of Histopathology Images: From Traditional Machine Learning to Deep Learning, 2017 |
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| , , , , , , , , , , , , und , Empowering Digital Pathology Applications through Explainable Knowledge Extraction Tools (2022), in: Journal of Digital Pathology |
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| , , , und , Enhanced EMG-based hand gesture classification in real-world scenarios: Mitigating dynamic factors with tempo-spatial wavelet transform and deep learning (2024), in: IEEE Transactions on Medical Robotics and Bionics, 6:3(1202--1211) |
| , , , und , Enhancing Gesture Classification Using Active EMG Band and Advanced Feature Extraction Technique (2023), in: IEEE Sensors Journal |
| , , , , und , Evaluation of methods for the extraction spatial muscle synergies, in: Frontiers in Neuroscience(763) |
| , , , , und , Evaluation of methods for the extraction spatial muscle synergies (2022), in: Frontiers in neuroscience |
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| , , , , , und , Experiences in the Creation of an Electromyography Database to Help Hand Amputated Persons, in: Proceedings of the 24th European Medical Informatics Conference - MIE2012, Pisa, Italy, 2012 |
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| , , , , und , Explainable AI-guided optimization of EMG channels and features for precise hand gesture classification: a SHAP-based study (2024), in: IEEE Transactions on Medical Robotics and Bionics |
| , , , und , Exploiting the PubMed Central repository to mine out a large multimodal dataset of rare cancer studies, in: SPIE Medical Imaging, Houston, TX, USA, 2020 |
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| , , , , , und , Exploring Publicly Accessible Optical Coherence Tomography Datasets: A Comprehensive Overview (2024), in: MDPI Diagostics |
[DOI] |
| , , und , Eye-hand coordination to improve grasp-type recognition in hand prostheses, in: Cybathlon Symposium, Zürich, Switzerland, 2020 |
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| , , , und , From NinaPro to MeganePro towards the natural control of myoelectric prosthetic hands, in: Cybathlon Symposium, Zurich, Switzerland, 2016 |
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| , , , , und , Functional Synergies Applied to a Publicly Available Dataset of Hand Grasps Show Evidence of Kinematic-Muscular Synergistic Control (2023), in: IEEE Access, Volume 11(108544 - 108560) |
[DOI] |
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| , , , , , , , , und , Gaze, behavioral, and clinical data for phantom limbs after hand amputation from 15 amputees and 29 controls (2020), in: Scientific Data, 7:1(1--14) |
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| , , , , , , , , , , , , und , Gaze, visual,myoelectric data of grasps for intelligent prosthetics (2020), in: Nature Scientific Data |
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| , , und , Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020 |
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| , , , und , H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression, in: ICCV 2021 workshop on Computational Challenges in Digital Pathology, 2021 |
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| , , , , , und , Hand Gesture Classification in Transradial Amputees Using the Myo Armband Classifier, in: 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob), Enschede, The Netherlands, Seiten 156 - 161, 2018 |
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| , und , Head-mounted eye gaze tracking devices: An overview of modern devices and recent advances (2018), in: Journal of Rehabilitation and Assistive Technologies Engineering, 5 |
[DOI] [URL] |
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| , , , , , , und , Identification and retrieval of prostate cancer cases using a content-based search tool (2019), in: Pathology Informatics |
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| , , und , Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content, in: MICCAI 2018 - Computational Pathology Workshop (COMPAY), Granada, Spain, 2018 |
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| , , , , und , Improving quality control of whole slide images by explicit artifact augmentation (2024), in: Scientific Reports, 14:1(17847) |
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| , , und , Improving Robotic Hand Prosthesis Control With Eye Tracking and Computer Vision: A Multimodal Approach Based on the Visuomotor Behavior of Grasping (2022), in: Frontiers in Artificial Intelligence(199) |
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| , , , , , , , und , Improving sEMG signals recognition accuracy using 3D compression and broad learning system (2025), in: SIGNAL, IMAGE AND VIDEO PROCESSING, 19:13 |
[DOI] |
| , , , , , , und , Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models (2023), in: Sci Rep:Article number: 19518 (2023) |
[DOI] |
| , , , , , , , , , , und , Increased fronto-temporal perfusion in bipolar disorder (2008), in: Journal of Affective Disorders:110(106-114) |
| , , , , , , , , , und , Intra-operative brain tumor detection with deep learning-optimized hyperspectral imaging, in: Optical Biopsy XXI: Toward Real-Time Spectroscopic Imaging and Diagnosis, SPIE, Seiten 74--92, 2023 |
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| , , , , und , Kinematic synergies of hand grasps, in: ESB 2019, Vienna, Austria, 2019 |
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