자연주의적 탐구조사(Naturalistic Inquiry)

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

https://link.springer.com/content/pdf/10.2307%2F3343168.pdf

Development as Freedom

The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene, nonrigid object structures, object-to-object and object-to-scene occlusions, and camera motion. Tracking is usually performed in the context of higher-level applications that require the location and/or shape of the object in every frame. Typically, assumptions are made to constrain the tracking problem in the context of a particular application. In this survey, we categorize the tracking methods on the basis of the object and motion representations used, provide detailed descriptions of representative methods in each category, and examine their pros and cons. Moreover, we discuss the important issues related to tracking including the use of appropriate image features, selection of motion models, and detection of objects.

/pdf/object-tracking-a-survey-3706dclxb5.pdf

Object tracking: A survey

In this paper, we propose a novel explicit image filter called guided filter. Derived from a local linear model, the guided filter computes the filtering output by considering the content of a guidance image, which can be the input image itself or another different image. The guided filter can be used as an edge-preserving smoothing operator like the popular bilateral filter [1], but it has better behaviors near edges. The guided filter is also a more generic concept beyond smoothing: It can transfer the structures of the guidance image to the filtering output, enabling new filtering applications like dehazing and guided feathering. Moreover, the guided filter naturally has a fast and nonapproximate linear time algorithm, regardless of the kernel size and the intensity range. Currently, it is one of the fastest edge-preserving filters. Experiments show that the guided filter is both effective and efficient in a great variety of computer vision and computer graphics applications, including edge-aware smoothing, detail enhancement, HDR compression, image matting/feathering, dehazing, joint upsampling, etc.

/pdf/guided-image-filtering-5atmpsksoa.pdf

Guided Image Filtering

ICTD has become a truly global undertaking, bringing together north and south, rich and poor, rural and urban, researcher and practitioner, technologist and social scientist—all striving to work toward a better life for the least privileged.

Information and Communication Technologies for Development

A vision-based controller provides translational and rotational control signals to a computer or other input driven device. The controller includes a tracked object, positioned in space and having at least a first reference point and a second reference point. The tracked object is capable of three dimensional rotational and translational movement. At least one imaging device, positioned at a distance from the tracked object, generates an image of the tracked object, at plural succeeding times. A processor unit receives the image, comprised of pixel values, from the imaging device; identifies pixels corresponding to a current center of the tracked object, the first reference point and the second reference point; determines a current dimension (i.e., size or radius) of the tracked object; calculates a translational and rotational displacement of the tracked object based on the above information; and generates control signals in accordance with the transitional and rotational displacement.

Vision-based six-degree-of-freedom computer input device

The present invention is embodied in a system and method for efficiently and efficiently performing automated vision tracking, such as tracking human head movement and facial movement. The system and method of the present invention fuses results of multiple sensing modalities to achieve robust digital vision tracking The system and method effectively fuses together the results of multiple vision processing modalities for performing tracking tasks in order to achieve robust vision tracking. The approach integrates reports from several distinct vision processing procedures in a probabilistically coherent manner by performing inferences about the location and/or motion of objects that considers both the individual reports about targets provided by visual processing modalities, as well as inferences about the context-sensitive accuracies of the reports. The context-sensitive accuracies are inferred by observing evidence with relevance to the reliabilities of the different methods.

A system and method for tracking objects by fusing results of multiple sensing modalities

This paper examines the social and political challenges related to the implementation of information and communication technology (ICT) kiosk projects for rural development in India. Specifically, the paper focuses on the Akshaya project, a franchise of rural computer-service kiosks, which was implemented in Kerala as a public-private sector collaboration. The Akshaya project has the twin goals of social development through increased access to computers for rural people and financial viability through market-driven entrepreneurship. Using interview and participant observation methods, we examine the challenges that state actors and entrepreneurs face in simultaneously addressing social and financial sustainability. The preliminary evidence suggests that there is a tension between these goals at a macro level (within the state) and a micro level (for entrepreneurs and potential consumers) that makes it difficult to run a financially self-sustaining ICT kiosk project that also meets social development goals. The paper demonstrates that the implementation of ICTs for development is not simply a technical process of delivering services to the poor, but is a highly political process that involves tradeoffs and prioritization of particular goals to attain sustainability. Branding this project is a challenge for the state and entrepreneurs due to consumer perceptions of what development is, with particular expectations of state provided services, versus what business is.

Integrating Social Development and Financial Sustainability: The Challenges of Rural Computer Kiosks in Kerala

Public spending on computer centers in rural Indian public schools raise questions about the value of expensive modern technology in extremely resource-strapped environments Arguments for or against providing computers in low-income schools have appeared in policy circles, academia, teacher conferences, and philanthropic discussions, with passionate rhetoric from all sides We present the results of a qualitative study of computer-aided learning centers in schools catering primarily to Below Poverty Line (BPL) families in four districts of rural Karnataka, South India Here, we held a series of open-and close-ended discussions with parents of children from these schools on issues such as aspirations, quality of schooling, and the perception of computers more generally The research reveals a range of voices on hopes for the next generation, perceived value of computer courses and higher education, and the perceived changes in villages after the arrival of computers in their local schools It emerges that for many parents, the computer has an immense symbolic value--separate from its functional value--that is tied to social and economic ascendancy We find that this symbolic value derives from associations that parents imbibe from their various interactions with people using computers in a range of situations We find in our interviews a heightened sense of mystique over the technology and its potential, across people with varying levels of first-hand experience and understanding of computers We find that notions of change and hope are situated within an environment of great fear about the future of agriculture We argue here that this, alongside a widespread existing discourse about computers in media and public life in India, mostly emerging from urban middle-classes ideas around technology, help spur a strong sense of expectation that the computers can dramatically change social prospects even among the poorest and most excluded From competing with English as the gateway to power, to impacting dowry costs for female youth, interviews show a myriad of expectations from technology, creating what we see as a strong case for a nuanced look at the discourse and mythology of computers and technology in developing regions

https://link.springer.com/content/pdf/10.1007%2Fs10796-009-9172-1.pdf

Kentaro Toyama

Papers

Information and Communication Technologies for Development

Vision-based six-degree-of-freedom computer input device

A system and method for tracking objects by fusing results of multiple sensing modalities

Integrating Social Development and Financial Sustainability: The Challenges of Rural Computer Kiosks in Kerala

My child will be respected: Parental perspectives on computers and education in Rural India