CLASSIFICATION BASED ON SEMI-SUPERVISED LEARNING: A REVIEW

Semi-supervised learning is the class of machine learning that deals with the use of supervised and unsupervised learning to implement the learning process. Conceptually placed between labelled and unlabeled data. In certain cases, it enables the large numbers of unlabeled data required to be utilized in comparison with usually limited collections of labeled data. In standard classification methods in machine learning, only a labeled collection is used to train the classifier. In addition, labelled instances are difficult to acquire since they necessitate the assistance of annotators, who serve in an occupation that is identified by their label. A complete audit without a supervisor is fairly easy to do, but nevertheless represents a significant risk to the enterprise, as there have been few chances to safely experiment with it so far. By utilizing a large number of unsupervised inputs along with the supervised inputs, the semi-supervised learning solves this issue, to create a good training sample. Since semi-supervised learning requires fewer human effort and allows greater precision, both theoretically or in practice, it is of critical interest

ICR ANNUAL REPORT 2020 (Volume 27)[All Pages]

This Annual Report covers from 1 January to 31 December 202

Applied Cognitive Sciences

Cognitive science is an interdisciplinary field in the study of the mind and intelligence. The term cognition refers to a variety of mental processes, including perception, problem solving, learning, decision making, language use, and emotional experience. The basis of the cognitive sciences is the contribution of philosophy and computing to the study of cognition. Computing is very important in the study of cognition because computer-aided research helps to develop mental processes, and computers are used to test scientific hypotheses about mental organization and functioning. This book provides a platform for reviewing these disciplines and presenting cognitive research as a separate discipline

Future benefits and applications of intelligent on-board processing to VSAT services

The trends and roles of VSAT services in the year 2010 time frame are examined based on an overall network and service model for that period. An estimate of the VSAT traffic is then made and the service and general network requirements are identified. In order to accommodate these traffic needs, four satellite VSAT architectures based on the use of fixed or scanning multibeam antennas in conjunction with IF switching or onboard regeneration and baseband processing are suggested. The performance of each of these architectures is assessed and the key enabling technologies are identified

ICR ANNUAL REPORT 2022 (Volume 29)[All Pages]

This Annual Report covers from 1 January to 31 December 202

Electronic Imaging & the Visual Arts. EVA 2013 Florence

Important Information Technology topics are presented: multimedia systems, data-bases, protection of data, access to the content. Particular reference is reserved to digital images (2D, 3D) regarding Cultural Institutions (Museums, Libraries, Palace – Monuments, Archaeological Sites). The main parts of the Conference Proceedings regard: Strategic Issues, EC Projects and Related Networks & Initiatives, International Forum on “Culture & Technology”, 2D – 3D Technologies & Applications, Virtual Galleries – Museums and Related Initiatives, Access to the Culture Information. Three Workshops are related to: International Cooperation, Innovation and Enterprise, Creative Industries and Cultural Tourism

ICR ANNUAL REPORT 2019 (Volume 26)[All Pages]

This Annual Report covers from 1 January to 31 December 201

A Spoken Dialogue System for Enabling Comfortable Information Acquisition and Consumption

早大学位記番号:新8137早稲田大

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task