Abstract: Out-of-distribution (OoD) semantic segmentation aims to recognize pixels of classes undefined in the training dataset. Existing methods mostly focus on training the model to fit real OoD ...
Abstract: Semantic segmentation is critical in remote sensing applications such as urban planning, disaster management, and environmental monitoring. However, segmenting complex satellite images ...
This repository contains the official Pytorch implementation of training & evaluation code and the trained models for Offset Learning & OffSeg. Offset Learning —— An efficient plug-and-play semantic ...
You followed the SEO playbook. You carefully selected keywords, analyzed competing content, and published long‑form articles that filled gaps in coverage for dozens of topics. Yet your Google rankings ...
Earlier, at the "Papers with Code" website, I could find the leaderboard for semantic segmentation (e.g., for ADE20K dataset). But, the "Papers with Code" website has disappeared and attempt to go ...
Introduction: Weeds compete with crops for water, nutrients, and light, negatively impacting maize yield and quality. To enhance weed identification accuracy and meet the requirements of precision ...
Introduction: Rising global populations and climate change necessitate increased agricultural productivity. Most studies on rice panicle detection using imaging technologies rely on single-time-point ...
ABSTRACT: To address the challenges of morphological irregularity and boundary ambiguity in colorectal polyp image segmentation, we propose a Dual-Decoder Pyramid Vision Transformer Network (DDPVT-Net ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results