Results 41 to 50 of about 28,970 (210)
Galaxy morphology classification with densenet
Journal of Physics: Conference Series, 2023 Abstract The classification of galaxies has always been an essential topic in astronomy, which can help to understand how galaxies form and evolve. This paper uses an effective deep-learning architecture, DenseNet-201, to classify galaxy morphology.
openaire +1 more source
DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
Mağallaẗ Al-kūfaẗ Al-handasiyyaẗHair loss impacts approximately 80 million people in the United States and arises from factors such as aging, genetic predisposition, stress, and medication.
Nagesh +3 more
doaj +1 more source
RADNET: Radiologist Level Accuracy using Deep Learning for HEMORRHAGE detection in CT Scans
, 2018 We describe a deep learning approach for automated brain hemorrhage detection from computed tomography (CT) scans. Our model emulates the procedure followed by radiologists to analyse a 3D CT scan in real-world.
Grewal, Monika +3 more
core +1 more source
Advanced Electronic Materials, EarlyView.This work proposes a machine‐vision‐based tool for predicting the thickness of in‐line deposited perovskite films, enabling real‐time decision making to control deposition parameters. The workflow integrates perovskite deposition and annealing with uniformity analysis and minimodule fabrication.
Juan Pablo Velásquez +9 more
wiley +1 more source
SmartRay – An AI-Based Module for Medical Images Processing
Applied Medical Informatics, 2021 The emergence of the global pandemic of COVID-19 has generated a global acceleration in the sphere of digital transformation of medicine filed. Medical consultations have become a routine for everyone, but this can be improved with new technologies.
Sebastian Aurelian ŞTEFĂNIGĂ +1 more
doaj
Insights into Imaging, 2023 Objectives This study aimed to explore and develop artificial intelligence approaches for efficient classification of pulmonary nodules based on CT scans. Materials and methods A number of 1007 nodules were obtained from 551 patients of LIDC-IDRI dataset.
Mohamed Saied +3 more
doaj +1 more source
Densely Connected Networks with Multiple Features for Classifying Sound Signals with Reverberation
Sensors, 2023 In indoor environments, reverberation can distort the signalseceived by active noise cancelation devices, posing a challenge to sound classification. Therefore, we combined three speech spectral features based on different frequency scales into a densely
Zhuo Chen +5 more
doaj +1 more source
Deep Neural Network Architectures for Modulation Classification
, 2018 In this work, we investigate the value of employing deep learning for the task of wireless signal modulation recognition. Recently in [1], a framework has been introduced by generating a dataset using GNU radio that mimics the imperfections in a real ...
Gamal, Aly El, Liu, Xiaoyu, Yang, Diyu
core +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
Advanced Intelligent Discovery, EarlyView.The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Pairwise Confusion for Fine-Grained Visual Classification
, 2018 Fine-Grained Visual Classification (FGVC) datasets contain small sample sizes, along with significant intra-class variation and inter-class similarity.
A Dubey +8 more
core +1 more source