Demo Data from EDBT 2026 / reviewers in the wild / expert
Vishwas Udpikar
dblp:48/764
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 1994
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Computer networks · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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 |
Image and video coding · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video coding › image compression › lossy image compression
block truncation coding |
0.0 | 1 | 1987 | BTC Image Coding Using Vector Quantization · IEEE Trans. Commun. 1987 |
Image and video coding
image compression |
0.0 | 1 | 1987 | BTC Image Coding Using Vector Quantization · IEEE Trans. Commun. 1987 |
Image and video coding › quantization
vector quantization |
0.0 | 1 | 1987 | BTC Image Coding Using Vector Quantization · IEEE Trans. Commun. 1987 |
Image and video coding
bit rate reduction |
0.0 | 1 | 1987 | BTC Image Coding Using Vector Quantization · IEEE Trans. Commun. 1987 |
Methods — techniques the papers use, named apart from their topics
vector quantization · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1994 | A text-to-speech system for application by visually handicapped and illiterate
P. Bhaskararao, Venkata N. Peri, Vishwas Udpikar |
ICSLP | 3 |
| 1987 | BTC Image Coding Using Vector QuantizationabstractThis paper describes source encoding of the outputs of a block truncation coder (BTC), namely, the overhead statistical information and the truncated block. The statistical overhead and the truncated block exhibit properties which can be effectively used for their quantization as vectors. Vector quantization of these BTC outputs results into reduction of the bit rate of the coder. The bit rate reduces up to 1.5 bits/ pel if vector quantization is used on one of the outputs; i.e., either the overhead information or the truncated block. By vector quantizing both the BTC outputs the bit rate can he reduced up to 1.0 bits/pel without introducing many perceivable errors in the reconstructed output. Vishwas Udpikar, J. P. Raina |
IEEE Trans. Commun. | 1 |