Pelagian Restaurant Billing
Pelagian Restaurant Billing software has been developed for beer bars, fast food corners, restaurants, sweet corners, bakeries, ice-cream parlors, hotels, cafeterias, pizzerias, homes, counters, clubs, corporate catering on the customized concept of KOT (Kitchen Order Token) system. The software allows making bills with and without the KOT system. This software provides a total item sale summary and daily sales summary without any burden. You can maintain stock regularly. Pelagian Restaurant Billing Software brings the complete solution for managing the restaurant in a faster and too easier way. This Windows-based software genuinely provides you with appropriate medium to fast entry and accurate output of desired input. We present your brief outline of this software which really helps you to understand it clearly. KOT will be split as per items serving the kitchen. like single order has multiple items that concern different kitchens will be directly sent to their kitchen printer.
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Cream
CREAM Finance is a DeFi ecosystem focused on providing lending, exchange, payment, and asset tokenization services. CREAM also operates a permissionless and open-source protocol so any other internet participant can be a part of the development of the network, instead of just using it or locking up funds in smart contracts for staking rewards. Financial inclusion is among CREAM'S primary goals. And the objective is to be able to achieve it without compromising the safety and security of each user and their assets. CREAM is established on the Ethereum blockchain, it can take advantage of smart contracts that can be used to run Ethereum Virtual Machines (EVM). Such a set-up also allows the CREAM project to have better composability than other DeFi projects. EVMs can also help community users develop their own decentralized applications (Dapps) on top of the network. However, there is very little detail on the community’s plans for such at the moment
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Amazon Rekognition
Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.
With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.
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Google Cloud Vision AI
Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.
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