Image segmentation using deep learning: A survey
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …
applications such as scene understanding, medical image analysis, robotic perception …
Improving semantic segmentation via decoupled body and edge supervision
Existing semantic segmentation approaches either aim to improve the object's inner
consistency by modeling the global context, or refine objects detail along their boundaries …
consistency by modeling the global context, or refine objects detail along their boundaries …
Survey on semantic segmentation using deep learning techniques
Semantic segmentation is a challenging task in computer vision systems. A lot of methods
have been developed to tackle this problem ranging from autonomous vehicles, human …
have been developed to tackle this problem ranging from autonomous vehicles, human …
In defense of pre-trained imagenet architectures for real-time semantic segmentation of road-driving images
Recent success of semantic segmentation approaches on demanding road driving datasets
has spurred interest in many related application fields. Many of these applications involve …
has spurred interest in many related application fields. Many of these applications involve …
Land-use map** for high-spatial resolution remote sensing image via deep learning: A review
Land-use map** (LUM) using high-spatial resolution remote sensing images (HSR-RSIs)
is a challenging and crucial technology. However, due to the characteristics of HSR-RSIs …
is a challenging and crucial technology. However, due to the characteristics of HSR-RSIs …
Temporally distributed networks for fast video semantic segmentation
We present TDNet, a temporally distributed network designed for fast and accurate video
semantic segmentation. We observe that features extracted from a certain high-level layer of …
semantic segmentation. We observe that features extracted from a certain high-level layer of …
[HTML][HTML] Dense-UNet: a novel multiphoton in vivo cellular image segmentation model based on a convolutional neural network
S Cai, Y Tian, H Lui, H Zeng, Y Wu… - Quantitative imaging in …, 2020 - ncbi.nlm.nih.gov
Background Multiphoton microscopy (MPM) offers a feasible approach for the biopsy in
clinical medicine, but it has not been used in clinical applications due to the lack of efficient …
clinical medicine, but it has not been used in clinical applications due to the lack of efficient …
Seamless scene segmentation
In this work we introduce a novel, CNN-based architecture that can be trained end-to-end to
deliver seamless scene segmentation results. Our goal is to predict consistent semantic …
deliver seamless scene segmentation results. Our goal is to predict consistent semantic …
Efficient semantic segmentation with pyramidal fusion
Emergence of large datasets and resilience of convolutional models have enabled
successful training of very large semantic segmentation models. However, high capacity …
successful training of very large semantic segmentation models. However, high capacity …
Video semantic segmentation via sparse temporal transformer
Currently, video semantic segmentation mainly faces two challenges: 1) the demand of
temporal consistency; 2) the balance between segmentation accuracy and inference …
temporal consistency; 2) the balance between segmentation accuracy and inference …