Unsupervised learning to detect loops using deep neural networks for visual SLAM system
Sign Up to like & getrecommendations! Published in 2017 at "Autonomous Robots"
DOI: 10.1007/s10514-015-9516-2
Abstract: This paper is concerned of the loop closure detection problem for visual simultaneous localization and mapping systems. We propose a novel approach based on the stacked denoising auto-encoder (SDA), a multi-layer neural network that autonomously… read more here.
Keywords: visual slam; slam; unsupervised learning; loops using ... See more keywords
Learning to detect lymphocytes in immunohistochemistry with deep learning
Sign Up to like & getrecommendations! Published in 2019 at "Medical image analysis"
DOI: 10.1016/j.media.2019.101547
Abstract: The immune system is of critical importance in the development of cancer. The evasion of destruction by the immune system is one of the emerging hallmarks of cancer. We have built a dataset of 171,166… read more here.
Keywords: learning; immunohistochemistry deep; deep learning; lymphocytes immunohistochemistry ... See more keywords
Using Machine Learning to Detect Fake Identities: Bots vs Humans
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2796018
Abstract: There are a growing number of people who hold accounts on social media platforms (SMPs) but hide their identity for malicious purposes. Unfortunately, very little research has been done to date to detect fake identities… read more here.
Keywords: machine learning; using machine; detect fake; learning detect ... See more keywords
Generative Deep Learning to Detect Cyberattacks for the IoT-23 Dataset
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2021.3140015
Abstract: The rapid growth of Internet of Things (IoT) is expected to add billions of IoT devices connected to the Internet. These devices represent a vast attack surface for cyberattacks. For example, these IoT devices can… read more here.
Keywords: generative deep; iot dataset; detect cyberattacks; deep learning ... See more keywords
Unsupervised Deep Learning to Detect Agitation from Videos in People with Dementia
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2022.3143990
Abstract: Behavioural symptoms of dementia present a significant risk within Long Term Care (LTC) homes, which face difficulties supporting residents and monitoring their safety with limited staffing resources. Many LTC facilities have installed video surveillance systems… read more here.
Keywords: detect agitation; unsupervised deep; people dementia; deep learning ... See more keywords
Learning to Detect Changes in Aerial Images in the Presence of Registration Errors
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3193375
Abstract: We present a convolutional neural network (CNN)-based approach for scene-level change detection in aerial images with registration errors. Thousands of aerial images and long videos are routinely acquired for monitoring large areas, such as forests… read more here.
Keywords: change detection; registration; registration errors; detect changes ... See more keywords
Learning to Detect Salient Object with Multi-source Weak Supervision.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2021.3059783
Abstract: High-cost pixel-level annotations makes it appealing to train saliency detection models with weak supervision. However, a single weak supervision source hardly contain enough information to train a well-performing model. To this end, we introduce a… read more here.
Keywords: salient object; weak supervision; supervision; source ... See more keywords
Learning to detect sexism: An evaluation of the effects of a brief video-based intervention using ROC analysis
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Psychology"
DOI: 10.3389/fpsyg.2022.1005633
Abstract: Empirical evidence for the effectiveness of interventions teaching lay people how to recognize sexism is scarce. The purpose of the present study was, thus, twofold: The first aim was to evaluate a brief intervention using… read more here.
Keywords: sexism; intervention using; analysis; sexist ... See more keywords