Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping

16 August 2021

Papers citing "Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping"

7 / 7 papers shown

Title
Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training data Irum Mehboob Li Sun Alireza Astegarpanah Rustam Stolkin UQCV 43 0 0 05 Nov 2024
SRAI: Towards Standardization of Geospatial AI Piotr Gramacki Kacper Le'sniara Kamil Raczycki Szymon Wo'zniak Marcin Przymus Piotr Szymañski 20 5 0 19 Oct 2023
Deep Spatiotemporal Clustering: A Temporal Clustering Approach for Multi-dimensional Climate Data Omar Faruque Francis Ndikum Nji Mostafa Cham Rohan Mandar Salvi Xue Zheng Jianwu Wang 11 3 0 27 Apr 2023
Mapping smallholder cashew plantations to inform sustainable tree crop expansion in Benin Leikun Yin Rahul Ghosh Chenxi Lin David Hale Christoph Weigl ... Jessica Till X. Jia Troy Mao Vipin Kumar Zhenong Jin 30 25 0 01 Jan 2023
Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach Chenxi Lin Liheng Zhong Xiao‐peng Song Jinwei Dong David B. Lobell Zhenong Jin AI4TS 14 92 0 19 Oct 2021
Segmentation of Satellite Imagery using U-Net Models for Land Cover Classification Priit Ulmas I. Liiv 32 79 0 05 Mar 2020
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 446 15,637 0 02 Nov 2015