AIMC Topic: Neural Networks, Computer

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Exploiting Pre-Trained Convolutional Neural Networks for the Detection of Nutrient Deficiencies in Hydroponic Basil.

Sensors (Basel, Switzerland)
Due to the integration of artificial intelligence with sensors and devices utilized by Internet of Things technology, the interest in automation systems has increased. One of the common features of both agriculture and artificial intelligence is reco...

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images.

Sensors (Basel, Switzerland)
Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathological pro...

DEDTI versus IEDTI: efficient and predictive models of drug-target interactions.

Scientific reports
Drug repurposing is an active area of research that aims to decrease the cost and time of drug development. Most of those efforts are primarily concerned with the prediction of drug-target interactions. Many evaluation models, from matrix factorizati...

Brain-optimized deep neural network models of human visual areas learn non-hierarchical representations.

Nature communications
Deep neural networks (DNNs) optimized for visual tasks learn representations that align layer depth with the hierarchy of visual areas in the primate brain. One interpretation of this finding is that hierarchical representations are necessary to accu...

Compression of molecular fingerprints with autoencoder networks.

Molecular informatics
Several binary molecular fingerprints were compressed using an autoencoder neural network. We analyzed the impact of compression on fingerprint performance in downstream classification and regression tasks. Classifiers trained on compressed fingerpri...

Artificial intelligence in wastewater treatment: A data-driven analysis of status and trends.

Chemosphere
Wastewater treatment is a complex process that involves many uncertainties, leading to fluctuations in effluent quality and costs, and environmental risks. Artificial intelligence (AI) can handle complex nonlinear problems and has become a powerful t...

Combined CNN and RNN Neural Networks for GPR Detection of Railway Subgrade Diseases.

Sensors (Basel, Switzerland)
Vehicle-mounted ground-penetrating radar (GPR) has been used to non-destructively inspect and evaluate railway subgrade conditions. However, existing GPR data processing and interpretation methods mostly rely on time-consuming manual interpretation, ...

Deep Voxelized Feature Maps for Self-Localization in Autonomous Driving.

Sensors (Basel, Switzerland)
Lane-level self-localization is essential for autonomous driving. Point cloud maps are typically used for self-localization but are known to be redundant. Deep features produced by neural networks can be used as a map, but their simple utilization co...

A Novel Steganography Method for Infrared Image Based on Smooth Wavelet Transform and Convolutional Neural Network.

Sensors (Basel, Switzerland)
Infrared images have been widely used in many research areas, such as target detection and scene monitoring. Therefore, the copyright protection of infrared images is very important. In order to accomplish the goal of image-copyright protection, a la...

Model discovery to link neural activity to behavioral tasks.

eLife
Brains are not engineered solutions to a well-defined problem but arose through selective pressure acting on random variation. It is therefore unclear how well a model chosen by an experimenter can relate neural activity to experimental conditions. H...