Review the state-of-the-art technologies of semantic segmentation based on deep learning
The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …
information and predict the semantic category of each pixel from a given label set. With the …
A survey on deep learning-based architectures for semantic segmentation on 2d images
I Ulku, E Akagündüz - Applied Artificial Intelligence, 2022 - Taylor & Francis
Semantic segmentation is the pixel-wise labeling of an image. Boosted by the extraordinary
ability of convolutional neural networks (CNN) in creating semantic, high-level and …
ability of convolutional neural networks (CNN) in creating semantic, high-level and …
UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery
Semantic segmentation of remotely sensed urban scene images is required in a wide range
of practical applications, such as land cover mapping, urban change detection …
of practical applications, such as land cover mapping, urban change detection …
Deep dual-resolution networks for real-time and accurate semantic segmentation of traffic scenes
Using light-weight architectures or reasoning on low-resolution images, recent methods
realize very fast scene parsing, even running at more than 100 FPS on a single GPU …
realize very fast scene parsing, even running at more than 100 FPS on a single GPU …
Deep dual-resolution networks for real-time and accurate semantic segmentation of road scenes
Semantic segmentation is a key technology for autonomous vehicles to understand the
surrounding scenes. The appealing performances of contemporary models usually come at …
surrounding scenes. The appealing performances of contemporary models usually come at …
U-net transformer: Self and cross attention for medical image segmentation
Medical image segmentation remains particularly challenging for complex and low-contrast
anatomical structures. In this paper, we introduce the U-Transformer network, which …
anatomical structures. In this paper, we introduce the U-Transformer network, which …
[HTML][HTML] ABCNet: Attentive bilateral contextual network for efficient semantic segmentation of Fine-Resolution remotely sensed imagery
Semantic segmentation of remotely sensed imagery plays a critical role in many real-world
applications, such as environmental change monitoring, precision agriculture …
applications, such as environmental change monitoring, precision agriculture …
Semantic segmentation for multiscale target based on object recognition using the improved Faster-RCNN model
D Jiang, G Li, C Tan, L Huang, Y Sun, J Kong - Future Generation …, 2021 - Elsevier
Image semantic segmentation has received great attention in computer vision, whose aim is
to segment different objects and provide them different semantic category labels so that the …
to segment different objects and provide them different semantic category labels so that the …
Bending reality: Distortion-aware transformers for adapting to panoramic semantic segmentation
Panoramic images with their 360deg directional view encompass exhaustive information
about the surrounding space, providing a rich foundation for scene understanding. To unfold …
about the surrounding space, providing a rich foundation for scene understanding. To unfold …
Adashare: Learning what to share for efficient deep multi-task learning
Multi-task learning is an open and challenging problem in computer vision. The typical way
of conducting multi-task learning with deep neural networks is either through handcrafted …
of conducting multi-task learning with deep neural networks is either through handcrafted …