Results 101 to 110 of about 5,457 (203)

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, Volume 2, Issue 4, August 2026.
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, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Revisiting CycleGAN for semi-supervised segmentation

CoRR, 2019
In this work, we study the problem of training deep networks for semantic image segmentation using only a fraction of annotated images, which may significantly reduce human annotation efforts. Particularly, we propose a strategy that exploits the unpaired image style transfer capabilities of CycleGAN in semi-supervised segmentation. Unlike recent works
Arnab Kumar Mondal, Aniket Agarwal, Jose Dolz, Christian Desrosiers   +3 more
openaire   +3 more sources

Xstainer: A Novel Virtual Staining Tool Powered by Advanced Deep Learning Techniques

Advanced Intelligent Systems, Volume 8, Issue 8, August 2026.
Xstainer is a deep learning–based virtual staining framework that converts hematoxylin and eosin‐stained whole slide images into multiple histochemical stains, including Masson's trichrome, Periodic acid‐Schiff, Jones methenamine silver, and Toluidine blue.
Fatma Nur Kinali, Derya Demir, Kutsev B. Ozyoruk, Yasin Almalioglu, Emre C. Kose, Drew F. K. Williamson, Gurdeniz Serin, G. Evren Keles, Banu S. Kumbaraci, Ceren Utku, Uguray P. Hacisalihoglu, Ilknur Turkmen, Figen Ozturk, Kayhan Basak, Yavuz Nuri Ertas, Mehmet Turan   +15 more
wiley   +1 more source

Additional file 1 of Depth image conversion model based on CycleGAN for growing tomato truss identification

, 2022
Additional file 1.
Dae-Hyun Jung (12892235), Taek Sung Lee (12892241), Cheoul Young Kim (12892238), Soo Hyun Park (12892244)   +3 more
core   +1 more source

A Lightweight and Erudite Automated BiLSTM‐Based Multi‐Cycle GAN for Retinal Blood Vessel and Optic Disc Segmentation in Fundus Images

Engineering Reports, Volume 8, Issue 8, August 2026.
This graphical abstract presents a lightweight and automated BiLSTM‐based Multi‐Cycle GAN framework for retinal blood vessel and optic disc segmentation in fundus images. Initially, fundus images undergo preprocessing, including green channel extraction, denoising, resizing, and dataset splitting.
Rasmita Kumari Mohanty, Amaravarapu Pramod Kumar, Yuvaraju Macha, Agraharam Siva Kumar, J. Srinivas, G. Shyama Chandra Prasad, Rajesh Kumar Verma, Shashi Kant   +7 more
wiley   +1 more source

The Optimization of Illustration Design in Cultural and Creative Products for Liaoning Region Under Intelligent Generative Adversarial Network

IEEE Access
This study explores the application of intelligent Generative Adversarial Networks (GANs) in illustration design and cultural and creative product design in Liaoning.
Minghui Niu, Ying Zhou
doaj   +1 more source

Cyclegan for Eeg Artifact Removal

Electroencephalogram (EEG) signals are often contaminated by electrooculogram (EOG) and electromyogram (EMG) artifacts, even in controlled environments. Traditional signal processing methods for artifact removal have notable limitations, and the potential of classical or deep machine learning algorithms for this task remains largely underexplored.
Guir, Abdelbaki, Filho, Israel Jesus Santos, Hamami-Mitiche, Latifa, Laleg-Kirati, Taous-Meriem   +3 more
openaire   +2 more sources

Predicting compositional changes of organic-inorganic hybrid materials with Augmented CycleGAN

, 2021
The tuned model used in Predicting compositional changes of organic-inorganic hybrid materials with Augmented ...
Qianxiang Ai
core   +1 more source

DT/MARS-CycleGAN: Improved Object Detection for MARS Phenotyping Robot

, 2023
Robotic crop phenotyping has emerged as a key technology to assess crops' morphological and physiological traits at scale. These phenotypical measurements are essential for developing new crop varieties with the aim of increasing productivity and dealing
Li, Zhengkun, Li, Changying, Liu, David, Wu, Zihao   +3 more
core  

Unsupervised Deep Learning for Synthetic CT Generation from CBCT Images for Proton and Carbon Ion Therapy for Paediatric Patients

Sensors
Image-guided treatment adaptation is a game changer in oncological particle therapy (PT), especially for younger patients. The purpose of this study is to present a cycle generative adversarial network (CycleGAN)-based method for synthetic computed ...
Matteo Pepa, Siavash Taleghani, Giulia Sellaro, Alfredo Mirandola, Francesca Colombo, Sabina Vennarini, Mario Ciocca, Chiara Paganelli, Ester Orlandi, Guido Baroni, Andrea Pella   +10 more
doaj   +1 more source