VLSI architecture design approaches for real-time video processing

This paper discusses the programmable and dedicated approaches for real-time video processing applications. Various VLSI architecture including the design examples of both approaches are reviewed. Finally, discussions of several practical designs in real-time video processing applications are then considered in VLSI architectures to provide significant guidelines to VLSI designers for any further real-time video processing design works

Neighbor cache prefetching for multimedia image and video processing

Cache performance is strongly influenced by the type of locality embodied in programs. In particular, multimedia programs handling images and videos are characterized by a bidimensional spatial locality, which is not adequately exploited by standard caches. In this paper we propose novel cache prefetching techniques for image data, called neighbor prefetching, able to improve exploitation of bidimensional spatial locality. A performance comparison is provided against other assessed prefetching techniques on a multimedia workload (with MPEG-2 and MPEG-4 decoding, image processing, and visual object segmentation), including a detailed evaluation of both the miss rate and the memory access time. Results prove that neighbor prefetching achieves a significant reduction in the time due to delayed memory cycles (more than 97% on MPEG-4 with respect to 75% of the second performing technique). This reduction leads to a substantial speedup on the overall memory access time (up to 140% for MPEG-4). Performance has been measured with the PRIMA trace-driven simulator, specifically devised to support cache prefetching

Programmable image associative memory using an optical disk and a photorefractive crystal

The optical disk is a computer-addressable binary storage medium with very high capacity. More than 10^10 bits of information can be recorded on a 12-cm-diameter optical disk. The natural two-dimensional format of the data recorded on an optical disk makes this medium particularly attractive for the storage of images and holograms, while parallel access provides a convenient mechanism through which such data may be retrieved. In this paper we discuss a closed-loop optical associative memory based on the optical disk. This system incorporates image correlation, using photorefractive media to compute the best association in a shift-invariant fashion. When presented with a partial or noisy version of one of the images stored on the optical disk, the optical system evolves to a stable state in which those stored images that best match the input are temporally locked in the loop

What is Computational Intelligence and where is it going?

What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with ``computational intelligence'' in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary), their applications, and selected fashionable pattern recognition methods. At present CI has no comprehensive foundations and is more a bag of tricks than a solid branch of science. The change of focus from methods to challenging problems is advocated, with CI defined as a part of computer and engineering sciences devoted to solution of non-algoritmizable problems. In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions. Grand challenges on both sides of this spectrum are addressed

Vision Science and Technology at NASA: Results of a Workshop

A broad review is given of vision science and technology within NASA. The subject is defined and its applications in both NASA and the nation at large are noted. A survey of current NASA efforts is given, noting strengths and weaknesses of the NASA program

NASA JSC neural network survey results

A survey of Artificial Neural Systems in support of NASA's (Johnson Space Center) Automatic Perception for Mission Planning and Flight Control Research Program was conducted. Several of the world's leading researchers contributed papers containing their most recent results on artificial neural systems. These papers were broken into categories and descriptive accounts of the results make up a large part of this report. Also included is material on sources of information on artificial neural systems such as books, technical reports, software tools, etc

Proposal of a health care network based on big data analytics for PDs

Health care networks for Parkinson's disease (PD) already exist and have been already proposed in the literature, but most of them are not able to analyse the vast volume of data generated from medical examinations and collected and organised in a pre-defined manner. In this work, the authors propose a novel health care network based on big data analytics for PD. The main goal of the proposed architecture is to support clinicians in the objective assessment of the typical PD motor issues and alterations. The proposed health care network has the ability to retrieve a vast volume of acquired heterogeneous data from a Data warehouse and train an ensemble SVM to classify and rate the motor severity of a PD patient. Once the network is trained, it will be able to analyse the data collected during motor examinations of a PD patient and generate a diagnostic report on the basis of the previously acquired knowledge. Such a diagnostic report represents a tool both to monitor the follow up of the disease for each patient and give robust advice about the severity of the disease to clinicians