Cargando…
Exploiting Concepts of Instance Segmentation to Boost Detection in Challenging Environments
In recent years, due to the advancements in machine learning, object detection has become a mainstream task in the computer vision domain. The first phase of object detection is to find the regions where objects can exist. With the improvements in deep learning, traditional approaches, such as slidi...
Autores principales: | Hashmi, Khurram Azeem, Pagani, Alain, Liwicki, Marcus, Stricker, Didier, Afzal, Muhammad Zeshan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9144693/ https://www.ncbi.nlm.nih.gov/pubmed/35632112 http://dx.doi.org/10.3390/s22103703 |
Ejemplares similares
-
Survey and Performance Analysis of Deep Learning Based Object Detection in Challenging Environments
por: Ahmed, Muhammad, et al.
Publicado: (2021) -
CasTabDetectoRS: Cascade Network for Table Detection in Document Images with Recursive Feature Pyramid and Switchable Atrous Convolution
por: Hashmi, Khurram Azeem, et al.
Publicado: (2021) -
Attention-Guided Disentangled Feature Aggregation for Video Object Detection
por: Muralidhara, Shishir, et al.
Publicado: (2022) -
Contrastive Learning for 3D Point Clouds Classification and Shape Completion
por: Nazir, Danish, et al.
Publicado: (2021) -
Three-Dimensional Reconstruction from a Single RGB Image Using Deep Learning: A Review
por: Khan, Muhammad Saif Ullah, et al.
Publicado: (2022)