Demo Data from EDBT 2026 / reviewers in the wild / expert
Stephen D. Isard
dblp:71/1137
· DBLP profile ↗
6ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4Graphics, computer vision, multimedia, augmented reality and games · 4Theory of computation · 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 |
Computational photography and imaging · 50% Image and video processing · 50% | |
| Theoretical computer science
1 paper |
Computational complexity · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › image filtering
scale-aware filtering |
0.0 | 1 | 1995 | Adaptive Scale Filtering: A General Method for Obtaining Shape From Texture · IEEE Trans. Pattern Anal. Mach. Intell. 1995 |
Computational photography and imaging › shape and reflectance estimation
shape from texture |
0.0 | 1 | 1995 | Adaptive Scale Filtering: A General Method for Obtaining Shape From Texture · IEEE Trans. Pattern Anal. Mach. Intell. 1995 |
Computational complexity
computability theory |
0.0 | 1 | 1969 | Computability over Arbitrary Fields · STOC 1969 |
Methods — techniques the papers use, named apart from their topics
perspective projection · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Adaptive Scale Filtering: A General Method for Obtaining Shape From TextureabstractIntroduces adaptive scale filtering, a general method for deriving shape from texture under perspective projection without recourse to prior segmentation of the image into geometric texture elements (texels), and without thresholding of filtered images. If texels on a given surface can be identified in an image then the orientation of that surface can be obtained. However, there is no general characterization of texels for arbitrary textures. Furthermore, even if the size and shape of texels on the surface is invariant with regard to position, perspective projection ensures that the size and shape of the corresponding image texels vary by orders of magnitude. Commencing with an initial set F/sub O/ of identical image filters, adaptive scale filtering iteratively derives a set F/sub N/ which contains a unique filter for each image position. Each element of F/sub N/ is tuned to the three-dimensional structure of the surface; that is, all image filters in F/sub N/ back-project to an identical shape and size on the surface. Thus image texels of various sizes, but associated with a single spatial scale on the surface, can be identified in different parts of the image. When combined with conventional shape from texture methods, edges derived using F/sub N/ provide accurate estimates of surface orientation. Results for planar surfaces are presented.> James V. Stone, Stephen D. Isard |
IEEE Trans. Pattern Anal. Mach. Intell. | 2 |
| 1992 | Evaluation of speech synthesis techniques in a comprehension task
H. A. Sydeserff, R. J. Caley, Stephen D. Isard, Mervyn A. Jack, Alex I. C. Monaghan, Jo Verhoeven |
Speech Commun. | 3 |
| 1991 | Evaluation of speech synthesis techniques in a comprehension task
H. A. Sydeserff, R. J. Caley, Stephen D. Isard, Mervyn A. Jack, Alex I. C. Monaghan, Jo Verhoeven |
EUROSPEECH | 3 |
| 1991 | Automatic diphone segmentation
P. A. Taylor, Stephen D. Isard |
EUROSPEECH | 2 |
| 1990 | Duration, pitch and diphones in the CSTR TTS systemabstractThis paper describes the prosodic processing and wave-form generation components of the text-to-speech system being developed at Edinburgh University's Centre for Speech Technology Research. Intonation is specified as a sequence of minimal descriptors whose locations are given in terms of syntactically-determined prosodic domains. A pitch contour is computed by converting the descriptors into a sequence of abstract targets whose absolute values depend on a specific speaker model. Duration is determined first at the level of the syllable by a neural network, then accommodated at the segment level according to the distributions observed in a phonetically balanced database. The output waveform is generated by LPC resynthesis of diphone units. Three methods of diphone segmentation are discussed. Nick Campbell 0001, Stephen D. Isard, Alex I. C. Monaghan, Jo Verhoeven |
ICSLP | 2 |
| 1969 | Computability over Arbitrary FieldsabstractIn most attempts to make precise the concept of a computable function, or decidable predicate, over a field F, it is considered necessary that the elements of F should be in some sense effectively describable, and hence that F itself should be countable. This is the attitude taken in the study of computable fields (see Rabin1). Gabor T. Herman, Stephen D. Isard |
STOC | 2 |