Filter-based feature selection has become crucial in many classification settings, especially object recognition, recently faced with learning strategies that originate thousands of cues. In this paper, we propose a method exploiting the convergence properties power series matrices, and introducing concept infinite (Inf-FS). Considering features as path among distributions letting these paths tend to an number permits investigation importance (relevance redundancy) when injected into...

Feature selection is playing an increasingly significant role with respect to many computer vision applications spanning from object recognition visual tracking. However, most of the recent solutions in feature are not robust across different and heterogeneous set data. In this paper, we address issue proposing a probabilistic latent graph-based algorithm that performs ranking step while considering all possible subsets features, as paths on graph, bypassing combinatorial problem...

We propose a filtering feature selection framework that considers subsets of features as paths in graph, where node is and an edge indicates pairwise (customizable) relations among features, dealing with relevance redundancy principles. By two different interpretations (exploiting properties power series matrices relying on Markov chains fundamentals) we can evaluate the values (i.e., subsets) arbitrary lengths, eventually go to infinite, from which dub our Infinite Feature Selection...

The Feature Selection Library (FSLib) introduces a comprehensive suite of feature selection (FS) algorithms for MATLAB, aimed at improving machine learning and data mining tasks. FSLib encompasses filter, embedded, wrapper methods to cater diverse FS requirements. Filter focus on the inherent characteristics features, embedded incorporate within model training, assess features through performance metrics. By enabling effective selection, addresses curse dimensionality, reduces computational...

Authorship attribution (AA) aims at recognizing automatically the author of a given text sample. Traditionally applied to literary texts, AA faces now new challenge identity people involved in chat conversations. These share many aspects with spoken conversations, but approaches did not take it into account so far. Hence, this paper tries fill gap and proposes two novelties that improve effectiveness traditional for type data: first is adopt features inspired by Conversation Analysis (in...

Following recent advancements in computer-aided detection and diagnosis systems for colonoscopy, the automated reporting of colonoscopy procedures is set to further revolutionize clinical practice. A crucial yet underexplored aspect development these creation computer vision models capable autonomously segmenting full-procedure videos into anatomical sections procedural phases. In this work, we aim create first open-access dataset task propose a state-of-the-art approach, benchmarked against...

In an era where accumulating data is easy and storing it inexpensive, feature selection plays a central role in helping to reduce the high-dimensionality of huge amounts otherwise meaningless data. this paper, we propose graph-based method for that ranks features by identifying most important ones into arbitrary set cues. Mapping problem on affinity graph-where are nodes-the solution given assessing importance nodes through some indicators centrality, particular, Eigen-vector Centrality...

Object tracking is one of the most important tasks in many applications computer vision.Many methods use a fixed set features ignoring that appearance target object may change drastically due to intrinsic and extrinsic factors.The ability dynamically identify discriminative would help handling variability by improving performance.The contribution this work threefold.Firstly, paper presents collection several modern feature selection approaches selected among filter, embedded, wrapper...

Nonverbal communication is often referred to as body language, an expression that accounts for the major role plays in interaction, especially when it comes conveying socially and psychologically relevant information. Such a result of long evolutionary process has shaped brain be sensitive signals sent by co -located others more than any other signal environment (e.g., human voice one sounds requires lowest energy heard). Still, despite such history, people communicate increasingly...

The last decade has seen a revolution in the theory and application of machine learning pattern recognition. Through these advancements, variable ranking emerged as an active growing research area it is now beginning to be applied many new problems. rationale behind this fact that recognition problems are by nature main objective algorithm sort objects according some criteria, so that, most relevant items will appear early produced result list. Ranking methods can analyzed from two different...

In shape analysis and matching, it is often important to encode information about the relation between a given point other points on shape, namely, its context . To this aim, we propose theoretically sound efficient approach for simulation of discrete time evolution process that runs through all possible paths pairs surface represented as triangle mesh in setting. We demonstrate how construction can be used efficiently construct multiscale descriptor, called Discrete Time Evolution Process...

Identity safekeeping has recently become an important problem for the social web: as a case study, we focus here on instant messaging platforms, proposing novel soft-biometric cues user recognition and verification. Specifically, design set of features encoding effectively how person converses: since chats are crossbreeds written text face-to-face verbal communication, inherit equally from textual authorship attribution conversational analysis speech. Importantly, our ignore completely...

This article proposes an automatic approach - based on nonverbal speech features aimed at the discrimination between depressed and non-depressed speakers. The experiments have been performed over one of largest corpora collected for such a task in literature (62 patients diagnosed with depression 54 healthy control subjects), especially when it comes to data where speakers as by professional psychiatrists. results show that can be accuracy 75% error analysis shows chances correct...

Interacting via text chats can be considered as a hybrid type of communication, in which textual information delivery follows turn-taking dynamics, resembling spoken interactions. An interesting research question is whether personality observed chats, similarly happening face-to-face exchanges. After an encouraging preliminary work on Skype, this study we have set up our own chat service key-logging functionalities been activated, so that the timings each key pressing measured. Using...

Identity safekeeping on chats has recently become an important problem social networks. One of the most issues is identity theft, where impostors steal a person, substituting her in chats, order to have access private information. In literature, been addressed by designing sets features which capture way person interacts through chats. However, such approaches perform well only long term, after conversation performed, this problem, since early turns conversation, much information can be...

This article presents the School Attachment Monitor, a novel interactive system that can reliably administer Manchester Child Story Task (a standard psychiatric test for assessment of attachment in children) without supervision trained professionals. problems children cause significant mental health issues and costs to society which technology has potential reduce. SAM collects, through instrumented doll-play games, enough information allow human assessor manually identify status children....

In the last decade new ways of shopping online have increased possibility buying products and services more easily faster than ever. this context, personality is a key determinant in decision making consumer when shopping. The two main reasons are: firstly, person's choices are influenced by psychological factors like impulsiveness, secondly, some consumers may be susceptible to impulse purchases others. To best our knowledge, impact on advertisements has been largely neglected at level...

Connectomics is gaining increasing interest in the scientific and clinical communities. It consists deriving models of structural or functional brain connections based on some local measures. Here we focus connectivity as detected by diffusion MRI. Connectivity matrices are derived from microstructural indices obtained 3D-SHORE. Typically, graphs used for inferring node properties that allow identifying those nodes play a prominent role network. This information can then be to detect network...