AIMC Topic: Neural Networks, Computer

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Shape Classification Using a Single Seal-Whisker-Style Sensor Based on the Neural Network Method.

Sensors (Basel, Switzerland)
Seals, sea lions, and other aquatic animals rely on their whiskers to identify and track underwater targets, offering valuable inspiration for the development of low-power, portable, and environmentally friendly sensors. Here, we design a single seal...

Dense Convolutional Neural Network-Based Deep Learning Pipeline for Pre-Identification of Circular Leaf Spot Disease of Leaves Using Optical Coherence Tomography.

Sensors (Basel, Switzerland)
Circular leaf spot (CLS) disease poses a significant threat to persimmon cultivation, leading to substantial harvest reductions. Existing visual and destructive inspection methods suffer from subjectivity, limited accuracy, and considerable time cons...

TriCAFFNet: A Tri-Cross-Attention Transformer with a Multi-Feature Fusion Network for Facial Expression Recognition.

Sensors (Basel, Switzerland)
In recent years, significant progress has been made in facial expression recognition methods. However, tasks related to facial expression recognition in real environments still require further research. This paper proposes a tri-cross-attention trans...

Non-Intrusive System for Honeybee Recognition Based on Audio Signals and Maximum Likelihood Classification by Autoencoder.

Sensors (Basel, Switzerland)
Artificial intelligence and Internet of Things are playing an increasingly important role in monitoring beehives. In this paper, we propose a method for automatic recognition of honeybee type by analyzing the sound generated by worker bees and drone ...

Modeling and Optimization of Ellagic Acid from Chebulae Fructus Using Response Surface Methodology Coupled with Artificial Neural Network.

Molecules (Basel, Switzerland)
The dried ripe fruit of Retz. is a common Chinese materia medica, and ellagic acid (EA), isolated from the plant, is an important bioactive component for medicinal purposes. This study aimed to delineate the optimal extraction parameters for extract...

VAIV bio-discovery service using transformer model and retrieval augmented generation.

BMC bioinformatics
BACKGROUND: There has been a considerable advancement in AI technologies like LLM and machine learning to support biomedical knowledge discovery.

Intrinsic sense of touch for intuitive physical human-robot interaction.

Science robotics
The sense of touch is a property that allows humans to interact delicately with their physical environment. This article reports on a technological advancement in intuitive human-robot interaction that enables an intrinsic robotic sense of touch with...

Benchmarking brain-computer interface algorithms: Riemannian approaches vs convolutional neural networks.

Journal of neural engineering
To date, a comprehensive comparison of Riemannian decoding methods with deep convolutional neural networks for EEG-based brain-computer interfaces remains absent from published work. We address this research gap by using MOABB, The Mother Of All BCI ...

Leveraging 3D convolutional neural network and 3D visible-near-infrared multimodal imaging for enhanced contactless oximetry.

Journal of biomedical optics
SIGNIFICANCE: Monitoring oxygen saturation ( ) is important in healthcare, especially for diagnosing and managing pulmonary diseases. Non-contact approaches broaden the potential applications of measurement by better hygiene, comfort, and capabilit...

Artificial intelligence-based pulmonary embolism classification: Development and validation using real-world data.

PloS one
This paper presents an artificial intelligence-based classification model for the detection of pulmonary embolism in computed tomography angiography. The proposed model, developed from public data and validated on a large dataset from a tertiary hosp...