Search results for "intelligence"
showing 10 items of 6959 documents
Adversarial Attack’s Impact on Machine Learning Model in Cyber-Physical Systems
2020
Deficiency of correctly implemented and robust defence leaves Internet of Things devices vulnerable to cyber threats, such as adversarial attacks. A perpetrator can utilize adversarial examples when attacking Machine Learning models used in a cloud data platform service. Adversarial examples are malicious inputs to ML-models that provide erroneous model outputs while appearing to be unmodified. This kind of attack can fool the classifier and can prevent ML-models from generalizing well and from learning high-level representation; instead, the ML-model learns superficial dataset regularity. This study focuses on investigating, detecting, and preventing adversarial attacks towards a cloud dat…
Temporal Denoising of Kinect Depth Data
2012
The release of the Microsoft Kinect has attracted the attention of researchers in a variety of computer science domains. Even though this device is still relatively new, its recent applications have shown some promising results in terms of replacing current conventional methods like the stereo-camera for robotics navigation, multi-camera system for motion detection and laser scanner for 3D reconstruction. While most work around the Kinect is on how to take full advantage of its capabilities, so far only a few studies have been carried out on the limitations of this device and fewer that provide solutions to enhance the precision of its measurements. In this paper, we review and analyse curr…
Extraction et évaluation de caractéristiques adaptées pour la classification du Lentigo à partir d’images de Microscopie Confocale
2019
International audience; La détection de cancer de la peau est l’un des défis de ces dernières décennies. Par ailleurs, diverses techniques d’imagerie ont pour objectif d’aider à la reconnaissance de ces pathologies malignes en contexte clinique. La Microscopie Confocale par Réflectance est un exemple de technique d’imagerie adaptée à la détection de maladie de la peau sur laquelle nous nous basons pour la détection de Lentigo. Les travaux présentés dans cet article portent sur la classification de ces images en trois catégories : sain, bénin et malin. Dans ce but, nous proposons et évaluons deux méthodes d’extraction de caractéristiques basées sur les descripteurs d’Haralick pour l’une et s…
Artificial intelligence in the diagnosis of pediatric allergic diseases.
2020
Abstract: Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decision support, care delivery, and chronic care management have been identified within the healthcare areas that could benefit from introducing AI. In pediatric allergy research, the recent developments in AI approach provided new perspectives for characterizing the heterogeneity of allergic diseases among patients. Moreover, the increasing use of electronic health records and personal healthcare records highlighted the relevance of AI in …
Artificial Intelligence in Medicine: Today and Tomorrow
2020
Artificial intelligence-powered medical technologies are rapidly evolving into applicable solutions for clinical practice. Deep learning algorithms can deal with increasing amounts of data provided by wearables, smartphones, and other mobile monitoring sensors in different areas of medicine. Currently, only very specific settings in clinical practice benefit from the application of artificial intelligence, such as the detection of atrial fibrillation, epilepsy seizures, and hypoglycemia, or the diagnosis of disease based on histopathological examination or medical imaging. The implementation of augmented medicine is long-awaited by patients because it allows for a greater autonomy and a mor…
Linear Feature Extraction for Ranking
2018
We address the feature extraction problem for document ranking in information retrieval. We then propose LifeRank, a Linear feature extraction algorithm for Ranking. In LifeRank, we regard each document collection for ranking as a matrix, referred to as the original matrix. We try to optimize a transformation matrix, so that a new matrix (dataset) can be generated as the product of the original matrix and a transformation matrix. The transformation matrix projects high-dimensional document vectors into lower dimensions. Theoretically, there could be very large transformation matrices, each leading to a new generated matrix. In LifeRank, we produce a transformation matrix so that the generat…
Integration of large-area optical imagers for biometric recognition and touch in displays
2021
In recent years there has been an increasing interest to integrate optical sensing in mobile displays, for instance, for biometric fingerprint scanning functionality. There are several routes to incorporate optical fingerprint functionality within the full display area, each with their own benefits and challenges. Here we investigate the different integration routes using large-area, ultra-thin imagers based on organic photodiodes.
A Dataset of Annotated Omnidirectional Videos for Distancing Applications
2021
Omnidirectional (or 360°) cameras are acquisition devices that, in the next few years, could have a big impact on video surveillance applications, research, and industry, as they can record a spherical view of a whole environment from every perspective. This paper presents two new contributions to the research community: the CVIP360 dataset, an annotated dataset of 360° videos for distancing applications, and a new method to estimate the distances of objects in a scene from a single 360° image. The CVIP360 dataset includes 16 videos acquired outdoors and indoors, annotated by adding information about the pedestrians in the scene (bounding boxes) and the distances to the camera of some point…
Decentralized classification in societies of autonomous and heterogenous robots
2011
This paper addresses the classification problem for a set of autonomous robots that interact with each other. The objective is to classify agents that “behave” in “different way”, due to their own physical dynamics or to the interaction protocol they are obeying to, as belonging to different “species”. This paper describes a technique that allows a decentralized classification system to be built in a systematic way, once the hybrid models describing the behavior of the different species are given. This technique is based on a decentralized identification mechanism, by which every agent classifies its neighbors using only local information. By endowing every agent with such a local classifie…
Dog behaviour classification with movement sensors placed on the harness and the collar
2021
Dog owners’ understanding of the daily behaviour of their dogs may be enhanced by movement measurements that can detect repeatable dog behaviour, such as levels of daily activity and rest as well as their changes. The aim of this study was to evaluate the performance of supervised machine learning methods utilising accelerometer and gyroscope data provided by wearable movement sensors in classification of seven typical dog activities in a semi-controlled test situation. Forty-five middle to large sized dogs participated in the study. Two sensor devices were attached to each dog, one on the back of the dog in a harness and one on the neck collar. Altogether 54 features were extracted from th…