Service allows you to issue an unlimited number of virtual cards and top them up with crypto for online purchases and advertising platforms: Facebook Ads, Google Ads, Microsoft Ads, TikTok Ads, etc. ⠀ Our mission stands by helping business owners and digital marketers to effectively scale up by using all-in-one financial service.⠀ No need in piles of documents to open an account and issue cards, now you can make it in 2 clicks.⠀ ⠀ Key benefits of e.pn:⠀ • Trusted US cards for media buying⠀ We work with reliable US partners and offer 52 BINs specially for advertising.⠀⠀ • from 2.5% fee on your deposit⠀ Get cashback on your first deposit fee up to $10K.⠀ • Manage your campaigns easily with auto-refill⠀ Never worry about not having enough balance for ad payments.⠀ • Perfect Team Flow⠀ Issue cards for your team, manage cash flow and see transactions in real time.
Low fees, intuitive UI, quick responses from the support. I recommend!
A good partner for traffic arbitrage, a pleasant price and a quick card issue
Convenient service with virtual cards at affordable prices. A great advantage is that you can use cryptocurrencies, which saves you from problems. I paid for subscriptions to video services, as well as other various services, without any issues, everything was done quickly and on time. The good customer support team responded promptly.
Based on our record, WordNet seems to be more popular. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
TL;DR: The authors pretrain the model to classify images into Wordnet synsets[a] that appear in the caption, using a standard Cross Entropy loss. They keep the number of classes relatively small by removing any synsets that don't show up in captions at least 500 times in the dataset. It seems to work well. My immediate question is: Why not classify among the entire hierarchy of all Wordnet synsets? --- [a]... - Source: Hacker News / 2 months ago
To operationalize this intuition, the Microsoft and UC Berkeley researchers use WordNet and Wiktionary to augment the text in image-text pairs. The concept itself is augmented for isolated concepts, such as the class labels in ImageNet, whereas for captions (such as from GCC), the least common noun phrase is augmented. Equipped with this additional structured knowledge, contrastively pretrained models exhibit... - Source: dev.to / 4 months ago
If you like this, definitely check out WordNet (https://wordnet.princeton.edu/). - Source: Hacker News / 6 months ago
I didn't understand well what you meant, but maybe this site can help you: https://wordnet.princeton.edu/. Source: over 1 year ago
What I'd do is work with a huge database like WordNet and then try to "extrapolate" BIP39 to 4096 words by creating queries against WordNet to obtain words meeting the constraints you'd like to keep. Source: over 1 year ago
VerbAce - VerbAce-Pro is an easy-to-use Desktop Translation Software. Translate in a mouse click
MyBrocard - Brocard allows you to create an unlimited number of virtual cards for paying for advertising and other online payments, manage a team of buyers, choose from 20+ bins for various tasks, and enjoy convenient API for integrations.
WordWeb - One-click lookup in any almost any Windows program; Hundreds of thousands of definitions and synonyms; The latest international English words; Works offline, or reference to Wikipedia and web references.
PST.NET - Virtual payment cards for online shopping and advertising
Artha - Artha is a handy thesaurus based on WordNet with distinct features like global hotkey look-up...
ABcard - ABcard - service allows you to issue an unlimited number of cards to pay for advertising accounts. 3 unique BINs for any work tasks, management of a team of media buyers inside a personal account and complete anonymity when paying for traffic.