AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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Exploring hyperspectral anomaly detection with human vision: A small target aware detector.

Neural networks : the official journal of the International Neural Network Society
Hyperspectral anomaly detection (HAD) aims to localize pixel points whose spectral features differ from the background. HAD is essential in scenarios of unknown or camouflaged target features, such as water quality monitoring, crop growth monitoring ...

Dynamic graph consistency and self-contrast learning for semi-supervised medical image segmentation.

Neural networks : the official journal of the International Neural Network Society
Semi-supervised medical image segmentation endeavors to exploit a limited set of labeled data in conjunction with a substantial corpus of unlabeled data, with the aim of training models that can match or even exceed the efficacy of fully supervised s...

A fully value distributional deep reinforcement learning framework for multi-agent cooperation.

Neural networks : the official journal of the International Neural Network Society
Distributional Reinforcement Learning (RL) extends beyond estimating the expected value of future returns by modeling its entire distribution, offering greater expressiveness and capturing deeper insights of the value function. To leverage this advan...

Enhancing space-time video super-resolution via spatial-temporal feature interaction.

Neural networks : the official journal of the International Neural Network Society
The target of space-time video super-resolution (STVSR) is to increase both the frame rate (also referred to as the temporal resolution) and the spatial resolution of a given video. Recent approaches solve STVSR using end-to-end deep neural networks....

A universal network strategy for lightspeed computation of entropy-regularized optimal transport.

Neural networks : the official journal of the International Neural Network Society
Optimal transport (OT) is an effective tool for measuring discrepancies in probability distributions and histograms of features. To reduce its high computational complexity, entropy-regularized OT is proposed, which is computed through Sinkhorn algor...

Rethinking the optimization objective for transferable adversarial examples from a fuzzy perspective.

Neural networks : the official journal of the International Neural Network Society
Transferable adversarial examples, which are generated by transfer-based attacks, have strong adaptability for attacking a completely unfamiliar victim model without knowing its architecture, parameters and outputs. While current transfer-based attac...

Similarity-based context aware continual learning for spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
Biological brains have the capability to adaptively coordinate relevant neuronal populations based on the task context to learn continuously changing tasks in real-world environments. However, existing spiking neural network-based continual learning ...

Neurocontrol for fixed-length trajectories in environments with soft barriers.

Neural networks : the official journal of the International Neural Network Society
In this paper we present three neurocontrol problems where the analytic policy gradient via back-propagation through time is used to train a simulated agent to maximise a polynomial reward function in a simulated environment. If the environment inclu...

Plane coexistence behaviors for Hopfield neural network with two-memristor-interconnected neurons.

Neural networks : the official journal of the International Neural Network Society
Memristors are commonly used as the connecting parts of neurons in brain-like neural networks. The memristors, unlike the existing literature, possess the capability to function as both self-connected synaptic weights and interconnected synaptic weig...

Cluster synchronization of fractional-order two-layer networks and application in image encryption/decryption.

Neural networks : the official journal of the International Neural Network Society
In this paper, a type of fractional-order two-layer network model is constructed, wherein each layer in the network exhibits distinct topology. Subsequently, the cluster synchronization problem of fractional-order two-layer networks is investigated t...