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Detection and Segmentation of Glioma Tumors Utilizing a UNet Convolutional Neural Network Approach with Non-Subsampled Shearlet Transform

J. Comput. Biol.
The prompt and precise identification and delineation of tumor regions within glioma brain images are critical for mitigating the risks associated with this life-threatening ailment.
T. M, K. S, K. Sagayam, A. J
semanticscholar   +1 more source

Light Field Reconstruction Using Shearlet Transform in TensorFlow

2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2019
Shearlet Transform (ST) is one of the most effective approaches for light field reconstruction from Sparsely-Sampled Light Fields (SSLFs). This demo paper presents a comprehensive implementation of ST for light field reconstruction using one of the most popular machine learning libraries, i.e. Tensor Flow. The flexible architecture of TensorFlow allows
Yuan Gao 0008   +3 more
openaire   +2 more sources

Blind light field image quality assessment with tensor color domain and 3D shearlet transform

Signal Processing, 2023
Jianjun Xiang   +4 more
semanticscholar   +1 more source

Robust JPEG steganography based on DCT and SVD in nonsubsampled shearlet transform domain

Multimedia tools and applications, 2022
Xiaofeng Song   +3 more
semanticscholar   +1 more source

Multimodal medical image fusion based on nonsubsampled shearlet transform and convolutional sparse representation

Multimedia tools and applications, 2021
Lifang Wang   +6 more
semanticscholar   +1 more source

A Novel Hybrid Multimodal Medical Image Fusion Scheme Based on Non-subsampled Shearlet Transform

Circuits, systems, and signal processing
D. Sharma   +3 more
semanticscholar   +1 more source

MRI denoising using advanced NLM filtering with non-subsampled shearlet transform

Signal, Image and Video Processing, 2021
Abhishek Sharma, Vijayshri Chaurasia
semanticscholar   +1 more source

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