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Researcher Evidence Record

Emanuele Dalsasso

This bounded record lists 14 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include cs.CV, eess.IV, cs.LG work dated 2020 to 2025. The record describes sources and coverage; it makes no judgment about the person.

Compiled coverage vector

Measured lane counts only. Not a trust score or person verdict.

Identity 2 canonical identity row plus typed public identifiers Pith papers 14 attributed paper rows in the Pith corpus, itemized below Imported works 0 imported works beyond the paper ledger Current reviews 0 of 14 papers carrying a current Pith review; presence, not outcome Sourced citations 0 of 14 works with a source-named citation count Coauthors 24 distinct coauthors across shared paper rows
Enumerated paper scope: 3 fields (cs.CV, eess.IV, cs.LG) · 2020-2025 sources: authors, author_identifiers · paper_authors · author_works · current_verdicts · cited_works

A sourced case file for attributed work. It is neither a profile score nor a verdict about this researcher.

Attributed works

A bounded ledger from the Pith paper and imported-work queries. Counts and source confidence stay with each work.

  1. 2025 Pith paper

    SMARTIES: Spectrum-Aware Multi-Sensor Auto-Encoder for Remote Sensing Images

    cs.CV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  2. 2025 Pith paper

    CanadaFireSat: Toward high-resolution wildfire forecasting with multiple modalities

    cs.CV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  3. 2024 Pith paper

    Multi-Scale and Multimodal Species Distribution Modeling

    cs.LG provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  4. 2024 Pith paper

    POLO -- Point-based, multi-class animal detection

    cs.CV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  5. 2024 Pith paper

    Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation

    cs.CV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  6. 2023 Pith paper

    Leveraging Vision-Language Foundation Models for Fine-Grained Downstream Tasks

    cs.CV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  7. 2022 Pith paper

    Fast strategies for multi-temporal speckle reduction of Sentinel-1 GRD images

    eess.IV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  8. 2022 Pith paper

    Multi-temporal speckle reduction with self-supervised deep neural networks

    eess.IV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  9. 2021 Pith paper

    As if by magic: self-supervised training of deep despeckling networks with MERLIN

    cs.CV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  10. 2021 Pith paper

    Image Restoration for Remote Sensing: Overview and Toolbox

    eess.IV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  11. 2021 Pith paper

    Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentation

    eess.IV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  12. 2021 Pith paper

    Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning

    eess.IV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  13. 2020 Pith paper

    SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy

    cs.CV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  14. 2020 Pith paper

    SAR2SAR: a semi-supervised despeckling algorithm for SAR images

    eess.IV provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Emanuele Dalsasso
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.

Evidence apparatus

The machinery behind this record. Every lane states whether Pith measured it, did not query it, could not reach it, or withheld it.

LaneStateObservedBoundary and source
identity Measured 2 Canonical identity row plus public typed identifiers.
source=authors, author_identifiers
papers Measured 14 of 14 bounded rows Rows attributed to this author UUID in the Pith corpus.
source=paper_authors
works Measured zero 0 of 0 bounded rows Imported works not duplicated by the paper ledger.
source=author_works
reviews Measured zero 0 of 14 bounded rows Coverage count only. No review outcome is projected onto the person.
source=current_verdicts
citations Measured zero 0 of 14 bounded rows Counts remain itemized by work and source.
source=cited_works
coauthors Measured 24 of 14 bounded rows Shared-work edges from admitted paper rows.
source=paper_authors
account Unavailable No public count of 1 bounded rows Account metadata is separate from corpus evidence.
source=users.author_id
Public identity sources
  • name variant
    Emanuele Dalsasso     backfill
    confidence 0.6

identity history

Enumerated research scope

Fields and dates come only from enumerated, non-disputed Pith paper rows. They do not claim career completeness.

  • cs.CV7 rows
  • eess.IV6 rows
  • cs.LG1 rows
  • 20202 rows
  • 20214 rows
  • 20222 rows
  • 20231 rows
  • 20243 rows
  • 20252 rows
Shared-work index
Record scope

The work queries are bounded. Missing rows may mean measured zero, an unavailable source, a query that did not run, or private data that Pith withheld. The lane table keeps those cases separate.

Paper findings remain attached to papers. They do not become findings about this researcher.