Pith. sign in

REVIEW 1 cited by

Pseudocovering and digital covering spaces

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2306.01235 v1 pith:BCKI3BGW submitted 2023-06-02 math.GN

classification math.GN
keywords citecoveringdigitallocalpseudo-someimprovedisomorphism
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
abstract

The notions of a local $(k_0,k_1)$-isomorphism and a weakly local $(k_0,k_1)$-isomorphism play crucial roles in developing a digital $(k_0,k_1)$-covering space and a pseudo-$(k_0,k_1)$-covering space, respectively. In relation to the study of pseudo-$(k_0,k_1)$-covering spaces, since there are some works to be refined and improved in the literature, the recent paper \cite{H10} improved and corrected some mistakes occurred in the literature. One of the important things is that the notion of a pseudo-$(k_0,k_1)$-covering map in \cite{H6,H9} was revised to be more broadened in \cite{H10}. Thus this new version is proved to be equivalent to a weakly local $(k_0,k_1)$-isomorphic surjection \cite{H10}. The present paper contains some works in \cite{H10} and we only deals with $k$-connected digital images $(X, k)$.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. GS-CLIP: Zero-shot 3D Anomaly Detection by Geometry-Aware Prompt and Synergistic View Representation Learning

    cs.CV 2026-02 conditional novelty 5.0 of 10

    GS-CLIP boosts zero-shot 3D anomaly detection by feeding CLIP both rendered and depth views plus geometry-derived text prompts, setting new state-of-the-art results on four benchmarks.

Pith tools