Artificial Corner

JUNE 18, 2023

Advances in deep learning and other NLP techniques have helped solve some of these challenges and have led to significant improvements in performance of QA systems in recent years. A Categorical Archive of ChatGPT Failures (2023), Arxiv publications How good is ChatGPT on QA tasks? Unlike the original SQuAD dataset, SQuAD 2.0

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Viso.ai

DECEMBER 6, 2024

Object Detection with Deep Learning for traffic analytics with a video stream Vehicles can recognize the appearance of the cyclist, pedestrian, or car in front of them thanks to class-specific object detection. 2016) introduced a unified framework to detect both cyclists and pedestrians from images.

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Heartbeat

AUGUST 23, 2023

Carefully examining and categorizing these materials can be time-consuming and laborious. On the other hand, NLP-powered algorithms can quickly process and categorize massive amounts of data, minimizing the time necessary for initial case assessment and information retrieval. Artificial intelligence in law: The state of play 2016.

NLP 52

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Viso.ai

OCTOBER 7, 2024

billion tons of municipal solid waste was generated globally in 2016 with experts predicting a steep rise to 3.40 Waste Categorization : Based on the classification, the waste is sorted into predefined categories (e.g., As per the World Bank, 2.01 billion tons in 2050. However, truly effective waste management is no simple task.

Convolutional Neural Networks 52

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Heartbeat

FEBRUARY 2, 2024

COCO-QA: Shifting attention to COCO-QA, questions are categorized based on types such as color, counting, location, and object. This categorization lays the groundwork for nuanced evaluation, recognizing that different question types demand distinct reasoning strategies from VQA algorithms. Deep residual learning for image recognition.

Computer Vision 52

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. In 2017, the landmark paper “ Attention is all you need ” was published, which laid out a new deep learning architecture based on the transformer.

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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Deep learning models with multilayer processing architecture are now outperforming shallow or standard classification models in terms of performance [5]. Ensemble deep learning: A review. Uysal and Gunal, 2014).

BERT 52

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Viso.ai

FEBRUARY 28, 2023

Computer vision applications built using OpenCV and deep learning models – Viso Suite Who uses OpenCV? It was later supported by Willow Garage and the computer vision startup Itseez which Intel acquired in 2016. Body, hand, or facial movements can be recognized and categorized to assign a pre-defined category.

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Explosion

FEBRUARY 12, 2017

In this post, I’ll explain how to solve text-pair tasks with deep learning, using both new and established tips and technologies. The SNLI dataset is over 100x larger than previous similar resources, allowing current deep-learning models to be applied to the problem. This gives us two 2d arrays — one per sentence.

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Viso.ai

DECEMBER 18, 2023

YOLOv2 In 2016, Joseph Redmon and Ali Farhadi released YOLOv2, which could detect over 9000 object categories. Image Classification Classification involves categorizing an entire image without localizing the object present within the image. With this architecture, YOLOv1 surpassed R-CNN with a mean average precision (mAP) of 63.4

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Probably Approximately a Scientific Blog

JANUARY 12, 2021

In the last 5 years, popular media has made it seem that AI is nearly if not already solved by deep learning, with reports on super-human performance on speech recognition, image captioning, and object recognition.

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Unite.AI

SEPTEMBER 20, 2023

These are deep learning models used in NLP. Hugging Face , started in 2016, aims to make NLP models accessible to everyone. Machine learning is about teaching computers to perform tasks by recognizing patterns, while deep learning, a subset of machine learning, creates a network that learns independently.

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