AIMC Topic: Algorithms

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The capacity of feedforward neural networks.

Neural networks : the official journal of the International Neural Network Society
A long standing open problem in the theory of neural networks is the development of quantitative methods to estimate and compare the capabilities of different architectures. Here we define the capacity of an architecture by the binary logarithm of th...

Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.

Medical image analysis
Good quality of medical images is a prerequisite for the success of subsequent image analysis pipelines. Quality assessment of medical images is therefore an essential activity and for large population studies such as the UK Biobank (UKBB), manual id...

Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Tumors are continuously evolving biological systems, and medical imaging is uniquely positioned to monitor changes throughout treatment. Although qualitatively tracking lesions over space and time may be trivial, the development of clinicall...

Quantifying the effect of Jacobiasca lybica pest on vineyards with UAVs by combining geometric and computer vision techniques.

PloS one
With the increasing competitiveness in the vine market, coupled with the increasing need for sustainable use of resources, strategies for improving farm management are essential. One such effective strategy is the implementation of precision agricult...

Lyapunov Theory-Based Fusion Neural Networks for the Identification of Dynamic Nonlinear Systems.

International journal of neural systems
This paper introduces a novel fusion neural architecture and the use of a novel Lyapunov theory-based algorithm, for the online approximation of the dynamics of nonlinear systems. The proposed neural system, in combination with the proposed update ru...

Visual P300 Mind-Speller Brain-Computer Interfaces: A Walk Through the Recent Developments With Special Focus on Classification Algorithms.

Clinical EEG and neuroscience
Brain-computer interfaces are sophisticated signal processing systems, which directly operate on neuronal signals to identify specific human intents. These systems can be applied to overcome certain disabilities or to enhance the natural capabilities...

Flow network tracking for spatiotemporal and periodic point matching: Applied to cardiac motion analysis.

Medical image analysis
The accurate quantification of left ventricular (LV) deformation/strain shows significant promise for quantitatively assessing cardiac function for use in diagnosis and therapy planning. However, accurate estimation of the displacement of myocardial ...

Abdominal multi-organ segmentation with organ-attention networks and statistical fusion.

Medical image analysis
Accurate and robust segmentation of abdominal organs on CT is essential for many clinical applications such as computer-aided diagnosis and computer-aided surgery. But this task is challenging due to the weak boundaries of organs, the complexity of t...

Exploiting machine learning for end-to-end drug discovery and development.

Nature materials
A variety of machine learning methods such as naive Bayesian, support vector machines and more recently deep neural networks are demonstrating their utility for drug discovery and development. These leverage the generally bigger datasets created from...