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Peter F. Summons

dblp:219/9799 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0002-0672-2616ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Audio and music processing · 50% Image and video coding · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Hardware accelerators and domain-specific architectures · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › quantization › vector quantization
codebook design		 0.011993
Systolic codebook generation [speech recognition] · IEEE Trans. Speech Audio Process. 1993
Audio and music processing
speech recognition		 0.011993
Systolic codebook generation [speech recognition] · IEEE Trans. Speech Audio Process. 1993

Methods — techniques the papers use, named apart from their topics

linear predictive coding · 0.0clustering · 0.0
YearPublicationVenuePosition
2018 Diabetic Retinopathy Classification Using C4.5
Mira Park 0001, Peter F. Summons
 PKAW2
1995 Fetal Health Decision Support System
John Falconer, Peter F. Summons, Hernan Villanueva
 IEA/AIE2
1993 Systolic codebook generation [speech recognition]
abstract
Two systolic codebook generators which are based on finding clusters in a multidimensional space with a suitable dissimilarity measure are presented. They are implemented on two novel VLSI architectures. For segments of speech represented by a sequence of k linear-predictive-coding vectors, the first version finds r large clusters in time O(rk), and the second version finds the maximal r clusters in time O(r log k).>
Bryan Beresford-Smith, Jens Breckling, Heiko Schröder 0001, Peter F. Summons
 IEEE Trans. Speech Audio Process.4