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Your monitoring isn't a stack. It's a pile. Fix that.
Errors, performance, logs, uptime. One install, one invoice, one UI.
Replace Datadog, New Relic, and Sentry without adding three more dashboards.
Code release for "Detecting Twenty-thousand Classes
Detic (“Detecting Twenty-thousand Classes using Image-level Supervision”) is a large-vocabulary object detector that scales beyond fully annotated datasets by leveraging image-level labels. It decouples localization from classification, training a strong box localizer on standard detection data while learning classifiers from weak supervision and large image-tag corpora. A shared region proposal backbone feeds a flexible classification head that can expand to tens of thousands of categories without exhaustive box annotations. The system supports zero- or few-shot extension to novel categories via semantic embeddings and class name supervision, making “open-world” detection practical. ...
MANTI is a one-stop shop N-termini annotation & evaluation solution. MANTI was previously (un)known as muda.pl ahead of v3.7, the project was renamed to MANTI.pl with v3.7 on 2019-06-24.
It congregates information from different MaxQuant or DiaNN/MSFragger output files into a master file suitable explicitly for protein neo-termini analyses. The central anchor for the data congregation is the modificationSpecificPeptides.txt or diann-output.pr_matrix.tsv file - additional data is inferred...
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muda.pl was renamed to MANTI.pl with v3.7, project development can be tracked on the MANTI project page on sourceforge.net. Old versions remain here for archival purposes.
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muda.pl is an evaluation script (written in Perl) without great dependencies.
It congregates information from 4 different MaxQuant output files into a master file suitable explicitly for protein neo-termini analyses. The central anchor for the data...