Search Results for author:
Found 6 papers, 0 papers with code
Context-based Deep Learning Architecture with Optimal Integration Layer for Image Parsing
However, deep learning models are not fully capable of exploiting visual and contextual information simultaneously.
Deep Learning Model with GA based Feature Selection and Context Integration
The empirical analysis reveals that optimized visual features with global and local contextual information play a significant role to improve accuracy and produce stable predictions comparable to state-of-the-art deep CNN models.
Facial Expression Analysis under Partial Occlusion: A Survey
Automatic machine-based Facial Expression Analysis (FEA) has made substantial progress in the past few decades driven by its importance for applications in psychology, security, health, entertainment and human computer interaction.
Spatially Constrained Location Prior for Scene Parsing
Semantic context is an important and useful cue for scene parsing in complicated natural images with a substantial amount of variations in objects and the environment.
Superpixel based Class-Semantic Texton Occurrences for Natural Roadside Vegetation Segmentation
In this paper, we present a novel approach that generates class-semantic color-texture textons and aggregates superpixel based texton occurrences for vegetation segmentation in natural roadside images.
Density Weighted Connectivity of Grass Pixels in Image Frames for Biomass Estimation
Accurate estimation of the biomass of roadside grasses plays a significant role in applications such as fire-prone region identification.
