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Found 17 papers, 1 papers with code
Distributed Bayesian Inference for Large-Scale IoT Systems
Notably, throughout the experiments, there is an observed increase in memory usage with growing test set sizes, this increment is sublinear, demonstrating the proficiency of the classifier in memory resource management.
Artificial intelligence models to evaluate the impact of climate change on groundwater resources
Considering an aquifer located in northern Italy as a case study, the neural networks were trained to replicate observed groundwater levels by taking as input precipitation and temperature records, and in the case of the NARX also antecedent groundwater levels, on a monthly scale.
User lung cancer classification using efficientnet from ct scan images
Lung-EffNet is built based on the architecture of EfficientNet and further modified by adding top layers in the classification head of the model.
MLA-Net: Feature Pyramid Network with Multi-Level Local Attention for Object Detection
Abstract: Feature pyramid networks and attention mechanisms are the mainstream methods to improve the detection performance of many current models.
A Hybrid Deep Learning-Based Model for Detection of Electricity Losses Using Big Data in Power Systems
In this paper, we propose a hybrid DL model for detecting theft activity in EC data.
FEW SHOT CROP MAPPING USING TRANSFORMERS AND TRANSFER LEARNING WITH SENTINEL-2 TIME SERIES: CASE OF KAIROUAN TUNISIA
In this paper, we present an approach to land cover mapping from Sentinel-2 (S-2) satellite image time series using deep learning methods in the context of few shots in agricultural areas which aims to learn a classifier to recognize unseen classes during training with limited labelled examples.
Identification of Molecular Subtypes and a Prognostic Signature Based on Inflammation-Related Genes in Colon Adenocarcinoma
We finally used qRT–PCR to detect the expression levels of four genes in colon cancer cell lines and obtained results consistent with the prediction.
An integrated global airline hub network design with fleet planning
Despite designing a hub network for regional flights, designing a hub network for international flights is considerably different because of the high frequency of medium-, or long-haul flights.
Cascade and Fusion: A Deep Learning Approach for Camouflaged Object Sensing
The demand for the sensor-based detection of camouflage objects widely exists in biological research, remote sensing, and military applications.
Portrait Segmentation Using Ensemble of Heterogeneous Deep-Learning Models
In this paper, we propose a novel approach using an ensemble method by combining multiple heterogeneous deep-learning based portrait segmentation models to improve the segmentation performance.
Detection algorithm of defects on polyethylene gas pipe using image recognition
Aiming at the defects in the polyethylene (PE) gas pipeline, a defect detection algorithm based on image recognition is proposed.
Integrated optimization of railway freight operation planning and pricing based on carbon emission reduction policies
To reduce carbon emissions from inland freight, one way is to encourage rail transportation instead of truck transportation.
Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck
Abstract: Road boundary detection is an important part of the perception of autonomous driving.
Predicting the hydrogen release ability of LiBH4-based mixtures by ensemble machine learning
The prediction of hydrogen release ability is indispensable to evaluating hydrogen storage performance of LiBH4-based mixtures before experimentation.
dynamic Long Short-Term Memory Neural-Network-Based Indict Remaining-Useful-Life Prognosis for Satellite Lithium-ion Battery
On-line remaining-useful-life (RUL) prognosis is still a problem for satellite Lithium-ion (Li-ion) batteries.
High performing all-solid electrochemical capacitor using chitosan/poly(acrylamide-co-diallyldimethylammonium chloride) as anion conducting membranes
The aim of the present work is to demonstrate a novel alkaline anion-exchange membrane composed of chitosan (CS) and poly (acrylamid-co-diallyldimethylammonium chloride) (PAADDA) for electrical double layer capacitors (EDLCs).
Automated EEG-based Screening of Depression Using Deep Convolutional Neural Network
It was discovered in this research that the EEG signals from the right hemisphere are more distinctive in depression than those from the left hemisphere.
