AIMC Topic: Neural Networks, Computer

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Illuminating the Neural Landscape of Pilot Mental States: A Convolutional Neural Network Approach with Shapley Additive Explanations Interpretability.

Sensors (Basel, Switzerland)
Predicting pilots' mental states is a critical challenge in aviation safety and performance, with electroencephalogram data offering a promising avenue for detection. However, the interpretability of machine learning and deep learning models, which a...

Automated Cow Body Condition Scoring Using Multiple 3D Cameras and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Body condition scoring is an objective scoring method used to evaluate the health of a cow by determining the amount of subcutaneous fat in a cow. Automated body condition scoring is becoming vital to large commercial dairy farms as it helps farmers ...

A combined encoder-transformer-decoder network for volumetric segmentation of adrenal tumors.

Biomedical engineering online
BACKGROUND: The morphology of the adrenal tumor and the clinical statistics of the adrenal tumor area are two crucial diagnostic and differential diagnostic features, indicating precise tumor segmentation is essential. Therefore, we build a CT image ...

IMH-Net: a convolutional neural network for end-to-end EEG motor imagery classification.

Computer methods in biomechanics and biomedical engineering
As the main component of Brain-computer interface (BCI) technology, the classification algorithm based on EEG has developed rapidly. The previous algorithms were often based on subject-dependent settings, resulting in BCI needing to be calibrated for...

Foreground segmentation network using transposed convolutional neural networks and up sampling for multiscale feature encoding.

Neural networks : the official journal of the International Neural Network Society
Foreground segmentation algorithm aims to precisely separate moving objects from the background in various environments. However, the interference from darkness, dynamic background information, and camera jitter makes it still challenging to build a ...

Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computing.

Neural networks : the official journal of the International Neural Network Society
Recent work has shown that machine learning (ML) models can skillfully forecast the dynamics of unknown chaotic systems. Short-term predictions of the state evolution and long-term predictions of the statistical patterns of the dynamics ("climate") c...

Multi-task machine learning models for simultaneous prediction of tissue-to-blood partition coefficients of chemicals in mammals.

Environmental research
Tissue-to-blood partition coefficients (P) are crucial for assessing the distribution of chemicals in organisms. Given the lack of experimental data and laborious nature of experimental methods, there is an urgent need to develop efficient predictive...

Prompt tuning for parameter-efficient medical image segmentation.

Medical image analysis
Neural networks pre-trained on a self-supervision scheme have become the standard when operating in data rich environments with scarce annotations. As such, fine-tuning a model to a downstream task in a parameter-efficient but effective way, e.g. for...

Filter pruning for convolutional neural networks in semantic image segmentation.

Neural networks : the official journal of the International Neural Network Society
The remarkable performance of Convolutional Neural Networks (CNNs) has increased their use in real-time systems and devices with limited resources. Hence, compacting these networks while preserving accuracy has become necessary, leading to multiple c...

A survey on cancer detection via convolutional neural networks: Current challenges and future directions.

Neural networks : the official journal of the International Neural Network Society
Cancer is a condition in which abnormal cells uncontrollably split and damage the body tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical images play an indispensable role in detecting various cancers; however,...