Main

processing priority

3

site type

0 (generic, awaiting analysis)

review version

11

html import

20 (imported)

Events

first seen date

2024-10-21 08:07:24

expired found date

-

created at

2024-10-21 08:07:24

updated at

2024-10-21 08:07:24

Domain name statistics

length

29

crc

25938

tld

86

nm parts

0

nm random digits

0

nm rare letters

0

Connections

is subdomain of id

87719371 (github.io)

previous id

0

replaced with id

0

related id

-

dns primary id

0

dns alternative id

0

lifecycle status

0 (unclassified, or currently active)

Subdomains and pages

deleted subdomains

0

page imported products

0

page imported random

0

page imported parking

0

Error counters

count skipped due to recent timeouts on the same server IP

0

count content received but rejected due to 11-799

0

count dns errors

0

count cert errors

0

count timeouts

0

count http 429

0

count http 404

0

count http 403

0

count http 5xx

0

next operation date

-

Server

server bits

server ip

-

Mainpage statistics

mp import status

20

mp rejected date

-

mp saved date

-

mp size orig

20415

mp size raw text

5445

mp inner links count

0

mp inner links status

1 (no links)

Open Graph

title

description

Novel training methods that exploit the spatio-temporal structure of remote sensing data.

image

site name

author

updated

2026-03-02 21:31:40

raw text

Geography-Aware Self-Supervised Learning Geography-Aware Self-Supervised Learning Kumar Ayush* , Burak Uzkent* , Chenlin Meng* , Kumar Tanmay , Marshall Burke , David B. Lobell , Stefano Ermon Stanford University ICCV 2021 Paper arXiv Code Dataset Images over time concept in the Functional Map of the World (fMoW) dataset. The metadata associated with each image is shown underneath. We can see changes in contrast, brightness, cloud cover etc. in the images. These changes render spatially aligned images over time useful for constructing additional positives. Abstract Contrastive learning methods have significantly narrowed the gap between supervised and unsupervised learning on computer vision tasks. In this paper, we explore their application to geo-located datasets, e.g. remote sensing, where unlabeled data is often abundant but labeled data is scarce. We first show that due to their different c...

Text analysis

redirect type

0 (-)

block type

0 (no issues)

detected language

1 (English)

category id

Serwisy SEC (10)

index version

1

spam phrases

0

Text statistics

text nonlatin

0

text cyrillic

0

text characters

4132

text words

743

text unique words

318

text lines

77

text sentences

36

text paragraphs

9

text words per sentence

20

text matched phrases

0

text matched dictionaries

0

RSS

rss path

rss status

1 (priority 1 already searched, no matches found)

rss found date

-

rss size orig

0

rss items

0

rss spam phrases

0

rss detected language

0 (awaiting analysis)

inbefore feed id

-

inbefore status

0 (new)

Sitemap

sitemap path

sitemap status

1 (priority 1 already searched, no matches found)

sitemap review version

2

sitemap urls count

0

sitemap urls adult

0

sitemap filtered products

0

sitemap filtered videos

0

sitemap found date

-

sitemap process date

-

sitemap first import date

-

sitemap last import date

-