Работы, цитирующие эту работу

Работ: 4

Работа: ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data

1. Dynamic Focus on Tumor Boundaries: A Lightweight U-Net for MRI Brain Tumor Segmentation

   Kuldashboy Avazov, Sanjar Mirzakhalilov, Sabina Umirzakova +2

   СтатьяBrain Tumor Detection and ClassificationBioengineering2024Цитирований: 5

   ABIABI:AkademIndex/openalex/2024.article.000160

2. CT-HiffNet: A contour-texture hierarchical feature fusion network for cropland field parcel extraction from high-resolution remote sensing images

   Hao Wu, Junyang Xie, Weihao Deng +10

   СтатьяRemote Sensing in AgricultureComputers and Electronics in Agriculture2025Цитирований: 1

   ABIABI:AkademIndex/openalex/2025.article.000223

3. An Integrated Architecture for Colorectal Polyp Segmentation: The µ-Net Framework with Explainable AI

   Md Mehedi Hasan Emon, Proloy Kumar Mondal, Md Ariful Islam Mozumder +4

   СтатьяColorectal Cancer Screening and DetectionDiagnostics2025Цитирований: 1

   ABIABI:AkademIndex/openalex/2026.other.327022

4. Ct-Hiffnet: A Contour-Texture Hierarchical Feature Fusion Network for Cropland Field Parcel Extraction from High-Resolution Remote Sensing Images

   Hao Wu, Junyang Xie, Weihao Deng +9

   ПрепринтRemote Sensing in AgricultureSSRN Electronic Journal2024Цитирований: 0

   ABIABI:AkademIndex/openalex/2024.preprint.000241