A survey on deep learning techniques for image and video semantic segmentation
Image semantic segmentation is more and more being of interest for computer vision and
machine learning researchers. Many applications on the rise need accurate and efficient …
machine learning researchers. Many applications on the rise need accurate and efficient …
A review on deep learning techniques applied to semantic segmentation
Image semantic segmentation is more and more being of interest for computer vision and
machine learning researchers. Many applications on the rise need accurate and efficient …
machine learning researchers. Many applications on the rise need accurate and efficient …
Fsdr: Frequency space domain randomization for domain generalization
Abstract Domain generalization aims to learn a generalizable model from aknown'source
domain for variousunknown'target domains. It has been studied widely by domain …
domain for variousunknown'target domains. It has been studied widely by domain …
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 …
Contextual-relation consistent domain adaptation for semantic segmentation
Recent advances in unsupervised domain adaptation for semantic segmentation have
shown great potentials to relieve the demand of expensive per-pixel annotations. However …
shown great potentials to relieve the demand of expensive per-pixel annotations. However …
Semantics for robotic mapping, perception and interaction: A survey
For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …
require a deeper understanding of the world in which they operate. In robotics and related …
The use of plant models in deep learning: an application to leaf counting in rosette plants
Deep learning presents many opportunities for image-based plant phenotyping. Here we
consider the capability of deep convolutional neural networks to perform the leaf counting …
consider the capability of deep convolutional neural networks to perform the leaf counting …
Methods and datasets on semantic segmentation: A review
Semantic segmentation, also called scene labeling, refers to the process of assigning a
semantic label (eg car, people, and road) to each pixel of an image. It is an essential data …
semantic label (eg car, people, and road) to each pixel of an image. It is an essential data …
Underwater image co-enhancement with correlation feature matching and joint learning
Q Qi, Y Zhang, F Tian, QMJ Wu, K Li… - … on Circuits and …, 2021 - ieeexplore.ieee.org
In underwater scenes, degraded underwater images caused by wavelength-dependent light
absorption and scattering present huge challenges to vision tasks. Underwater image …
absorption and scattering present huge challenges to vision tasks. Underwater image …
Spatially invariant unsupervised object detection with convolutional neural networks
E Crawford, J Pineau - Proceedings of the AAAI Conference on Artificial …, 2019 - ojs.aaai.org
There are many reasons to expect an ability to reason in terms of objects to be a crucial skill
for any generally intelligent agent. Indeed, recent machine learning literature is replete with …
for any generally intelligent agent. Indeed, recent machine learning literature is replete with …