Results 81 to 90 of about 10,267 (252)

Average SSIM of two groups of images of MIT-5K.

, 2022
Average SSIM of two groups of images of MIT-5K.
Lihua Bi (2265031), Canlin Li (12700223), Jinjuan Zhu (12700226), Weizheng Zhang (6006350), Yan Liu (25061)   +4 more
core   +1 more source

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

SSIM comprarison: (a) the results of the first three images in Fig 7 measured in SSIM, (b) the results of the last three images in Fig 7 measured in SSIM.

, 2018
SSIM comprarison: (a) the results of the first three images in Fig 7 measured in SSIM, (b) the results of the last three images in Fig 7 measured in SSIM.
Guangyao Li (428714), Qiaochuan Chen (5745905), Li Xie (108913), Mang Xiao (163329), Lei Peng (260321)   +4 more
core   +1 more source

A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Md. Zahid Hasan, Taslima Ferdaus Shuva, Touhid Bhuiyan, Muhammad Ali Abdullah Almoyad, Nabil Anan Orka, Md. Tanvir Rahman, Risala Tasin Khan, M. Shamim Kaiser, Mohammad Ali Moni   +11 more
wiley   +1 more source

SSIM values of 20 random images of MIT-5K.

, 2022
SSIM values of 20 random images of MIT-5K.
Lihua Bi (2265031), Canlin Li (12700223), Jinjuan Zhu (12700226), Weizheng Zhang (6006350), Yan Liu (25061)   +4 more
core   +1 more source

NIRGB‐GS: Near‐Infrared Assisted Low‐Light Scene Reconstruction and Enhancement via Gaussian Splatting

Advanced Intelligent Systems, EarlyView.
This article proposes NIRGB‐GS, a multimodal 3DGS variant that enables reliable 3D reconstruction and normal‐light novel‐view synthesis for extremely low‐light scenes by fusing paired near‐infrared and noisy RGB captures. High‐SNR near‐infrared modality and modality‐specific appearance encoding together resolve the issues of unstable pose/geometry ...
Chengyun Yang, Yi Zhang, Yu Lei, Qiaofeng Li   +3 more
wiley   +1 more source

Effectiveness of the RIFE Algorithm in 3D Animation Motion Interpolation : A Case Study Approach

Jurnal Sisfokom
This study evaluates the performance of the Real-Time Intermediate Flow Estimation (RIFE) algorithm in enhancing the temporal continuity and perceptual quality of 3D-rendered animation.
Arie Rahmat Ramdhani, Ema Utami
doaj   +1 more source

Evaluación ambiental para la determinación del caudal ecológico mediante el método holístico MesoHABSIM y el estado de la calidad del río Pativilca en el área de influencia de la central hidroeléctrica Cahua, ubicada en el distrito Manás, provincia Cajatambo, departamento Lima, durante el 2019

, 2019
La Dirección de Evaluación Ambiental del OEFA realizó la presente evaluación con el objetivo de determinar el caudal ecológico mediante el método holístico MesoHABSIM y la preferencia de hábitat del «camarón de río» para lo cual también se evaluó la ...
Chuquisengo Picon, Llojan, Eneque Puicón, Armando Martín, Organismo de Evaluación y Fiscalización Ambiental. Dirección de Evaluación Ambiental. Subdirección de Sitios Impactados   +2 more
core  

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

MDSC: Unsupervised Multipath Decomposition and Synergistic Correction for Efficient Low‐Light Image Enhancement with Detail‐Aware Smoothing

Advanced Intelligent Systems, EarlyView.
This work proposes MDSC, an unsupervised low‐light enhancement framework integrating three core innovations: detail‐aware smoothing, multipath decomposition, and synergistic correction. It suppresses noise, handles rapid illumination variations, and prevents reflectance‐contrast amplification inherent to Retinex separation.
Yong Cheng, De Yu, Yongqi Yuan, Mengjie Ye, Huan Wang, Qian Zhang, Ge Jin   +6 more
wiley   +1 more source