Approximate biometrics are often required for effective online shopping experience, for example, for clothing, eyewear and footwear. We experimented with Mask-RCNN based object segmentation for measuring human feet with the intention of recommending appropriate footwear, which we talk about in this post.
I’ve been thinking about a few aspects of smart contracts and blockchain tech - especially public blockchain tech - and I have some lingering doubts that I’d like to capture here for any of you to attack.
(With contributions from Sita Krishnakumar, Vishwas Bhushan and Manoj Kumar)
I am going to write this topic in couple of blogs. So that reader will get complete exposure of oracle services providers, like Oraclize in particular. In my first blog post I will try to give a brief overview of Oracle services. Basically dealing with questions like, What are Oracles? What is Oraclize? What is the use of such services? Etc. In the subsequent blog, we will try to use the Oraclize service with our smart contract and further we will take a deeper look into, how it works under the hood?
Here at Imaginea Labs, we are exploring the true power of gpu-computing by analysing its way of launching a kernel, running 1000’s of thread blocks simultaneously, threads doing memory accesses in terms of global/shared and the optimized way to do so, doing atomic operation in threads when needed, optimizing threads to run more efficiently and faster.
In this post, we talk about cuda architecture and various experiments done on a use case with a brute-force approach to test and explore the gpu computation limits. We’ve had modest success in bringing out the best of gpu and faced some intriguing situations and results along the way.
Extracting text from PDF documents is a common pre-processing task for text analysis and NLP work. The main challenges tools face in extracting content from PDF files is that PDFs are composed of text, graphics and tabular structures encoded in a form designed for printing.
The distributed ledger protocol used by blockchains has resulted in systems where we do not have to place trust in particular parties involved in maintaining these ledgers. Moreover the ledgers are programmable with “smart contracts” - transactors whose state changes are recorded and validated on the blockchain. A collection of smart contracts describes a system that is expected to ensure certain invariants relevant to the domain are upheld. For example, an election system is expected to maintain voter confidentiality. While the code that describes these “smart contracts” is open for anyone to read, those who’re participating in the systems run by these smart contracts are not in general competent to evaluate them, with the OSS community being the sole eyes on the contracts being deployed. In this post, I examine how these smart contracts can provide “warranties” that are easier to ratify and describe clear and automatic consequences of violating the warranted properties.