Giacomo Donato Cascarano

According to our database1, Giacomo Donato Cascarano authored at least 21 papers between 2016 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
A Multi-modal Tool Suite for Parkinson's Disease Evaluation and Grading.
Proceedings of the Neural Approaches to Dynamics of Signal Exchanges, 2020

Task-Oriented Muscle Synergy Extraction Using An Autoencoder-Based Neural Model.
Inf., 2020

A Novel Approach Based on Region Growing Algorithm for Liver and Spleen Segmentation from CT Scans.
Proceedings of the Intelligent Computing Theories and Application, 2020

A Tversky Loss-Based Convolutional Neural Network for Liver Vessels Segmentation.
Proceedings of the Intelligent Computing Theories and Application, 2020

2019
A model-free technique based on computer vision and sEMG for classification in Parkinson's disease by using computer-assisted handwriting analysis.
Pattern Recognit. Lett., 2019

Biometric handwriting analysis to support Parkinson's Disease assessment and grading.
BMC Medical Informatics Decis. Mak., 2019

A low-cost vision system based on the analysis of motor features for recognition and severity rating of Parkinson's Disease.
BMC Medical Informatics Decis. Mak., 2019

A comparison between two semantic deep learning frameworks for the autosomal dominant polycystic kidney disease segmentation based on magnetic resonance images.
BMC Medical Informatics Decis. Mak., 2019

A neural network-based software to recognise blepharospasm symptoms and to measure eye closure time.
Comput. Biol. Medicine, 2019

An undercomplete autoencoder to extract muscle synergies for motor intention detection.
Proceedings of the International Joint Conference on Neural Networks, 2019

An Innovative Neural Network Framework for Glomerulus Classification Based on Morphological and Texture Features Evaluated in Histological Images of Kidney Biopsy.
Proceedings of the Intelligent Computing Methodologies - 15th International Conference, 2019

A Survey on Deep Learning in Electromyographic Signal Analysis.
Proceedings of the Intelligent Computing Methodologies - 15th International Conference, 2019

Detection and Segmentation of Kidneys from Magnetic Resonance Images in Patients with Autosomal Dominant Polycystic Kidney Disease.
Proceedings of the Intelligent Computing Theories and Application, 2019

2018
A comparison between ANN and SVM classifiers for Parkinson's disease by using a model-free computer-assisted handwriting analysis based on biometric signals.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

A Supervised Approach to Classify the Status of Bone Mineral Density in Post-Menopausal Women through Static and Dynamic Baropodometry.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Recognition and Severity Rating of Parkinson's Disease from Postural and Kinematic Features During Gait Analysis with Microsoft Kinect.
Proceedings of the Intelligent Computing Theories and Application, 2018

A Model-Free Computer-Assisted Handwriting Analysis Exploiting Optimal Topology ANNs on Biometric Signals in Parkinson's Disease Research.
Proceedings of the Intelligent Computing Theories and Application, 2018

A Deep Learning Approach for the Automatic Detection and Segmentation in Autosomal Dominant Polycystic Kidney Disease Based on Magnetic Resonance Images.
Proceedings of the Intelligent Computing Theories and Application, 2018

2017
A Nonlinear Autoencoder for Kinematic Synergy Extraction from Movement Data Acquired with HTC Vive Trackers.
Proceedings of the Advances in Intelligent Information Hiding and Multimedia Signal Processing, 2017

A Novel Approach in Combination of 3D Gait Analysis Data for Aiding Clinical Decision-Making in Patients with Parkinson's Disease.
Proceedings of the Intelligent Computing Theories and Application, 2017

2016
A Comprehensive Method for Assessing the Blepharospasm Cases Severity.
Proceedings of the Recent Trends in Image Processing and Pattern Recognition, 2016


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