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Record W2114185890 · doi:10.1109/lcn.2008.4664259

Energy-efficient transmission scheme of JPEG images over Visual Sensor Networks

2008· article· en· W2114185890 on OpenAlexaff
Abdelhamid Mammeri, Ahmed Khoumsi, Djemel Ziou, Brahim Hadjou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsJPEGDiscrete cosine transformComputer scienceQuantization (signal processing)Computer visionTransform codingBlock (permutation group theory)Energy (signal processing)Energy consumptionArtificial intelligenceTransmission (telecommunications)Data compressionImage (mathematics)MathematicsEngineering

Abstract

fetched live from OpenAlex

With Visual Sensor Networks (VSN), designers must respect strict constraints on energy consumption, which make compression standards, such as JPEG, not energy-beneficial to VSN. Our approach for tackling this constraint problem consists in adapting JPEG by exploiting the DCT energy compaction property. This exploitation is performed by processing only a portion of each block of 8 times 8 DCT coefficients of the captured image. This approach induces two conflicting effects. Indeed, reducing the size of the portion of DCT block presents the advantage of reducing the energy consumed for processing and transmitting an image, but it also presents the drawback of reducing the quality of the image received at the sink.We propose two methods to solve this conflict: a global method and a local method. In the global method, an optimal size is computed for all portions of DCT blocks of a whole image.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.732
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.223
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2008
Admission routes1
Has abstractyes

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