[HTML][HTML] Machine learning methods for sign language recognition: A critical review and analysis
Sign language is an essential tool to bridge the communication gap between normal and
hearing-impaired people. However, the diversity of over 7000 present-day sign languages …
hearing-impaired people. However, the diversity of over 7000 present-day sign languages …
Understanding deep learning techniques for image segmentation
The machine learning community has been overwhelmed by a plethora of deep learning--
based approaches. Many challenging computer vision tasks, such as detection, localization …
based approaches. Many challenging computer vision tasks, such as detection, localization …
A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection
Change detection (CD) aims to identify surface changes from bitemporal images. In recent
years, deep learning (DL)-based methods have made substantial breakthroughs in the field …
years, deep learning (DL)-based methods have made substantial breakthroughs in the field …
Deep spectral methods: A surprisingly strong baseline for unsupervised semantic segmentation and localization
L Melas-Kyriazi, C Rupprecht… - Proceedings of the …, 2022 - openaccess.thecvf.com
Unsupervised localization and segmentation are long-standing computer vision challenges
that involve decomposing an image into semantically-meaningful segments without any …
that involve decomposing an image into semantically-meaningful segments without any …
Unsupervised learning of image segmentation based on differentiable feature clustering
The usage of convolutional neural networks (CNNs) for unsupervised image segmentation
was investigated in this study. Similar to supervised image segmentation, the proposed CNN …
was investigated in this study. Similar to supervised image segmentation, the proposed CNN …
Autoregressive unsupervised image segmentation
In this work, we propose a new unsupervised image segmentation approach based on
mutual information maximization between different constructed views of the inputs. Taking …
mutual information maximization between different constructed views of the inputs. Taking …
A coarse-to-fine weakly supervised learning method for green plastic cover segmentation using high-resolution remote sensing images
Green plastic cover (GPC) is a kind of green plastic fine mesh primarily used for covering
construction sites and mitigating large amounts of dust during construction. Accurate GPC …
construction sites and mitigating large amounts of dust during construction. Accurate GPC …
Unsupervised object segmentation by redrawing
Object segmentation is a crucial problem that is usually solved by using supervised learning
approaches over very large datasets composed of both images and corresponding object …
approaches over very large datasets composed of both images and corresponding object …
Pixel and region level information fusion in membership regularized fuzzy clustering for image segmentation
Membership regularized fuzzy clustering methods apply an important prior that neighboring
data points should possess similar memberships according to an affinity/similarity matrix. As …
data points should possess similar memberships according to an affinity/similarity matrix. As …
Compositional transformers for scene generation
D Arad Hudson, L Zitnick - Advances in neural information …, 2021 - proceedings.neurips.cc
We introduce the GANformer2 model, an iterative object-oriented transformer, explored for
the task of generative modeling. The network incorporates strong and explicit structural …
the task of generative modeling. The network incorporates strong and explicit structural …