Performance Comparison of Depth Estimation Algorithms for Autonomous Systems

A 5.5 KB Excel file compares the performance of different depth estimation algorithms. The dataset, authored by Gobinda Chandra Sarker and last updated in April 2026, is hosted on figshare under a CC-BY-4.0 license. Its small size suggests it likely contains aggregated metrics or summary results from algorithm evaluations.

Use Cases

• Benchmarking depth estimation models based on performance metrics.
• Informing algorithm selection for obstacle avoidance systems in autonomous vehicles.
• Supporting research into efficient navigation for unmanned aerial vehicles (UAVs).

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• License is clearly defined as CC-BY-4.0, permitting reuse with attribution.
• Last update date is explicitly provided (2026-04-03).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Likely contains results from experimental comparisons of computer vision algorithms.

Time Range

Dataset last updated in April 2026; temporal coverage of underlying experiments is unknown.

Freshness

Last updated 2026-04-03 17:54:45; freshness should be verified.

Geography

Spatial coverage is unknown.