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 …
Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation
Abstract Recently, Neural Architecture Search (NAS) has successfully identified neural
network architectures that exceed human designed ones on large-scale image …
network architectures that exceed human designed ones on large-scale image …
Encoder-decoder with atrous separable convolution for semantic image segmentation
Spatial pyramid pooling module or encode-decoder structure are used in deep neural
networks for semantic segmentation task. The former networks are able to encode multi …
networks for semantic segmentation task. The former networks are able to encode multi …
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 …
Searching for efficient multi-scale architectures for dense image prediction
The design of neural network architectures is an important component for achieving state-of-
the-art performance with machine learning systems across a broad array of tasks. Much …
the-art performance with machine learning systems across a broad array of tasks. Much …
Computer vision for autonomous vehicles: Problems, datasets and state of the art
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
Playing for data: Ground truth from computer games
Recent progress in computer vision has been driven by high-capacity models trained on
large datasets. Unfortunately, creating large datasets with pixel-level labels has been …
large datasets. Unfortunately, creating large datasets with pixel-level labels has been …
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
In this work we address the task of semantic image segmentation with Deep Learning and
make three main contributions that are experimentally shown to have substantial practical …
make three main contributions that are experimentally shown to have substantial practical …
Enet: A deep neural network architecture for real-time semantic segmentation
The ability to perform pixel-wise semantic segmentation in real-time is of paramount
importance in mobile applications. Recent deep neural networks aimed at this task have the …
importance in mobile applications. Recent deep neural networks aimed at this task have the …