CNN-based encoder-decoder networks for salient object detection: A comprehensive review and recent advances
Convolutional neural network (CNN)-based encoder-decoder models have profoundly
inspired recent works in the field of salient object detection (SOD). With the rapid …
inspired recent works in the field of salient object detection (SOD). With the rapid …
Screen content quality assessment: Overview, benchmark, and beyond
Screen content, which is often computer-generated, has many characteristics distinctly
different from conventional camera-captured natural scene content. Such characteristic …
different from conventional camera-captured natural scene content. Such characteristic …
Towards large-scale small object detection: Survey and benchmarks
With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …
prominent advances in past years. However, such prosperity could not camouflage the …
An improved YOLOv5 model based on visual attention mechanism: Application to recognition of tomato virus disease
J Qi, X Liu, K Liu, F Xu, H Guo, X Tian, M Li… - … and electronics in …, 2022 - Elsevier
Traditional target detection methods cannot effectively screen key features, which leads to
overfitting and produces a model with a weak generalization ability. In this paper, an …
overfitting and produces a model with a weak generalization ability. In this paper, an …
Salient object detection in the deep learning era: An in-depth survey
As an essential problem in computer vision, salient object detection (SOD) has attracted an
increasing amount of research attention over the years. Recent advances in SOD are …
increasing amount of research attention over the years. Recent advances in SOD are …
Dense attention fluid network for salient object detection in optical remote sensing images
Despite the remarkable advances in visual saliency analysis for natural scene images
(NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains …
(NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains …
Scene segmentation with dual relation-aware attention network
In this article, we propose a Dual Relation-aware Attention Network (DRANet) to handle the
task of scene segmentation. How to efficiently exploit context is essential for pixel-level …
task of scene segmentation. How to efficiently exploit context is essential for pixel-level …
Structure-measure: A new way to evaluate foreground maps
Foreground map evaluation is crucial for gauging the progress of object segmentation
algorithms, in particular in the filed of salient object detection where the purpose is to …
algorithms, in particular in the filed of salient object detection where the purpose is to …
[HTML][HTML] Attention in psychology, neuroscience, and machine learning
Attention is the important ability to flexibly control limited computational resources. It has
been studied in conjunction with many other topics in neuroscience and psychology …
been studied in conjunction with many other topics in neuroscience and psychology …
Advanced deep-learning techniques for salient and category-specific object detection: a survey
Object detection, including objectness detection (OD), salient object detection (SOD), and
category-specific object detection (COD), is one of the most fundamental yet challenging …
category-specific object detection (COD), is one of the most fundamental yet challenging …