Carnegie Mellon, Qatar computing research presents arabic Speech Recognition by end-to-end, modular systems and human

Recent advances in automatic speech recognition (ASR) have achieved accuracy levels comparable to human transcribers, which led researchers to debate if the machine has reached human performance. Previous work focused on the English language and modular hidden Markov model-deep neural network (HMM-DNN) systems. In this paper, we perform a comprehensive benchmarking for end-to-end transformer ASR, modular HMM-DNN ASR, and human speech recognition (HSR) on the Arabic language and its dialects.

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Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene Graphs

Humans are able to form a complex mental model of the environment they move in. This mental model captures geometric and semantic aspects of the scene, describes the environment at multiple levels of abstractions (e.g., objects, rooms, buildings), includes static and dynamic entities and their relations (e.g., a person is in a room at a given time).

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Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation

Social relations are often used to improve recommendation quality when user-item interaction data is sparse in recommender systems. Most existing social recommendation models exploit pairwise relations to mine potential user preferences. However, real-life interactions among users are very complicated and user relations can be high-order. Hypergraph provides a natural way to model complex high-order relations, while its potentials for improving social recommendation are under-explored.

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Top 10 Computer Vision papers 2020

Even with everything that happened in the world this year, we still had the chance to see a lot of amazing research come out. Especially in the field of artificial intelligence and more precisely computer vision. Artificial intelligence and our understanding of the human brain and its link to AI is constantly evolving, showing promising applications in the soon future, which I will definitely cover. Here are my top 10 of the most interesting research papers of the year in computer vision, in case you missed any of them.

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11 programming books that can help you become a better programmer

A reading guide for those serious about programming. There’s no single programming book that will make you a better programmer. The best books to learn to code can vary based on what language you’re pursuing, so the sections below didn’t just focus on one language but eleven. Without further ado, here are some of the books every programmer should read.

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15 Free Data Science, Machine Learning & Statistics eBooks for 2021

We present a curated list of 15 free eBooks compiled in a single location to close out the year. Among other articles highlighting such materials, I have written a series of posts since the pandemic erupted, in the case that more people spending more time at home may result in more time for reading.

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A complete Learning Path to Data Labelling & Annotation (with Guide to 15 major Tools)

With the advancements in deep learning algorithms, computer vision and NLP have greatly evolved and done wonders around the world of AI. Along with this AutoML has also grown. This has led many industries to adopt AI smoothly and make efficient use of it in various use cases.

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How to use MuleSoft to send Slack Notifications when data changes

We all know that building content platforms is hard. You are constantly fighting misinformation, spam, and undesired ads—mostly from bots, the plague of the modern web. Some estimate that two-thirds of links posted on Twitter can come from bots.
So how can you fight them?

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5 papers on Face Recognition every Data Scientist should read

Face recognition, or facial recognition, is one of the largest areas of research within computer vision. We can now use face recognition to unlock our mobile phones, verify identification at security gates, and in some countries, make purchases. With the ability to make numerous processes more efficient, many companies invest into the research and development of facial recognition technology. This article will highlight some of that research and introduce five machine learning papers on face recognition. 

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2020 in Review | 10 AI papers that made an impact

Much of the world may be on hold, but AI research is still booming. The volume of peer-reviewed AI papers has grown by more than 300 percent over the last two decades, and attendance at AI conferences continues to increase significantly, according to the Stanford AI Index.

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Google at NeurIPS 2020

This week marks the beginning of the 34th annual Conference on Neural Information Processing Systems (NeurIPS 2020), the biggest machine learning conference of the year. Held virtually for the first time, this conference includes invited talks, demonstrations and presentations of some of the latest in machine learning research. As a Platinum Sponsor of NeurIPS 2020, Google will have a strong presence with more than 180 accepted papers, additionally contributing to and learning from the broader academic research community via talks, posters, workshops and tutorials.

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Introducing Caer — A GPU-accelerated Computer Vision Library

A Python library that changes the way your approach towards Machine VisionJason DsouzaJust now·4 min readCaer — GPU-accelerated Image & Video Processing. Image by Author.When I released Caer back in August of this year, I have received hundreds of emails from researchers and computer vision enthusiasts around the world thanking me for releasing the library. Their good (and bad) feedback pushed and motivated me to take the library to another level.

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