Search results for "LABOR"

Deep learning techniques for visual object tracking

2023

Visual object tracking plays a crucial role in various vision systems, including biometric analysis, medical imaging, smart traffic systems, and video surveillance. Despite notable advancements in visual object tracking over the past few decades, many tracking algorithms still face challenges due to factors like illumination changes, deformation, and scale variations. This thesis is divided into three parts. The first part introduces the visual object tracking problem and discusses the traditional approaches that have been used to study it. We then propose a novel method called Tracking by Iterative Multi-Refinements, which addresses the issue of locating the target by redefining the search…

Towards a deep-learning-based methodology for supporting satire detection

2021

This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers.

Design for invention: a framework for identifying emerging design–prior art conflict

2018

The increasing complexity of patented mechanical designs means that their novelty and inventive steps increasingly rely on interacting geometric features and how they contribute to device functions. These features and interactions are normally incorporated in patents through clear patent claims. However, patents can be difficult to interpret and understand for designers due to their legal terminologies. This suggests there is a need for greater awareness of relevant prior art amongst designers in terms of avoiding potential conflict. This paper presents a framework that helps designers obtain insight on relevant prior art and enables emerging design–prior art comparison. The framework mainl…

An Approach for the Design of Self-conscious Agent for Robotics

2010

Developing complex robotic systems endowed with self- conscious abilities and subjective experience is a hard requirement to face at design time. This paper deals with the development of robotic systems that do not own any a-priori knowledge of the environment they live in and proposes an agent-orientd design process for modelling and implementing such a systems by means of implementing the perception loop occurring between environment, body and brain during subjective experience. A case study dealing with a robocup setup is proposed in order to describe the design process activities and to illustrate the techniques for making the robot able to autonomously decide when an unknown situations…

[Radiomics and artificial intelligence: new frontiers in medicine.]

2020

Radiomics is a new frontier of medicine based on the extraction of quantitative data from radiological images which can not be seen by radiologist's naked eye and on the use of these data for the creation of clinical decision support systems. The long-term goal of radiomics is to improve the non-invasive diagnosis of focal and diffuse diseases of different organs by understanding links between extracted quantitative imaging data and the underlying molecular and pathological characteristics of lesions. In the last decade, several studies have highlighted the enormous potential of radiomics in both tumoral and non-tumoral diseases of many organs and systems including brain, lung, breast, gast…

Filling-in Gaps in Textured Images Using Bit-Plane Statistics

2008

In this paper we propose a novel approach for the texture analysis-synthesis problem, with the purpose to restore missing zones in greyscale images. Bit-plane decomposition is used, and a dictionary is build with bit-blocks statistics for each plane. Gaps are reconstructed with a conditional stochastic process, to propagate texture global features into the damaged area, using information stored in the dictionary. Our restoration method is simple, easy and fast, with very good results for a large set of textured images. Results are compared with a state-of-the-art restoration algorithm.

Clifford Rotors for Conceptual Representation in Chatbots

2013

In this abstract we introduce an unsupervised sub-symbolic natural language sentences encoding procedure aimed at catching and representing into a Chatbot Knowledge Base (KB) the concepts expressed by an user interacting with a robot. The chatbot KB is coded in a conceptual space induced from the application of the Latent Semantic Analysis (LSA) paradigm on a corpus of documents. LSA has the effect of decomposing the original relationships between elements into linearly-independent vectors. Each basis vector can be considered therefore as a "conceptual coordinate", which can be tagged by the words which better characterize it. This tagging is obtained by performing a (TF-IDF)-like weighting…

DAISY: a distributed architecture for intelligent SYstem

1997

Distributed perceptual systems are endowed with different kind of sensors, from which information flows to suitable modules to perform useful elaborations for decisions making. In this paper a new distributed architecture, named 'Distributed Architecture for Intelligent SYstem' (DAISY), is proposed. It is based on the concept of co-operating behavioral agents supervised by a 'Central Engagement Module'. This module integrates the processing of data coming from the behavioral agents with a symbolic level of representation, by the introduction of a 'conceptual space' intermediate analogue representation. The DAISY project is under development; experiments on navigation and exploration for an …

Symbolic Programming of Distributed Cyber-Physical Systems

Cyber-Physical Systems (CPSs) tightly integrate physical world phenomena and cyber aspects of computational units. The composition of physical, computational and communication systems demands different levels and types of abstraction as well as novel programming methodologies allowing for homogeneous programming, knowledge representation and exchange on heterogeneous devices. Current modeling approaches, frameworks and architectures result fairly inadequate to the task, especially when resource-constrained devices are involved. This work proposes symbolic computation as an effective solution to program resource constrained CPS devices with code maintaining strict ties to high-level specific…

Testing wearable IoT applications through sensor virtualization

2020

The development of distributed IoT applications requires the integration of data provided by different sensors embedded in multiple devices. As an example, an application for health monitoring in an assisted living scenario may include several wearable and fixed nodes each carrying different sensors and running specific code. Verifying that the application is properly working according to the specifications requires assessing that the code of each node behaves consistently in all the possible use cases. Tests involving sensor data may be difficult or costly to replicate realistically and this could also slow down the development of the application in its early stages. In this paper we intro…