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Embed, encode, attend, predict: The new deep learning formula for state-of-the-art NLP models

Explosion

now features deep learning models for named entity recognition, dependency parsing, text classification and similarity prediction based on the architectures described in this post. You can now also create training and evaluation data for these models with Prodigy , our new active learning-powered annotation tool. Bowman et al.

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Crack Detection in Concrete

Towards AI

Deep learning algorithms can be applied to solving many challenging problems in image classification. Therefore, Now we conquer this problem of detecting the cracks using image processing methods, deep learning algorithms, and Computer Vision. 1030–1033, 2016. View at: Publisher Site | Google Scholar R.

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Object Detection in 2024: The Definitive Guide

Viso.ai

The recent deep learning algorithms provide robust person detection results. However, deep learning models such as YOLO that are trained for person detection on a frontal view data set still provide good results when applied for overhead view person counting ( TPR of 95%, FPR up to 0.2% ).

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Top Computer Vision Tools/Platforms in 2023

Marktechpost

The system analyzes visual data before categorizing an object in a photo or video under a predetermined heading. One of the most straightforward computer vision tools, TensorFlow, enables users to create machine learning models for computer vision-related tasks like facial recognition, picture categorization, object identification, and more.

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Faster R-CNNs

PyImageSearch

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

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YOLOv4: A Fast and Efficient Object Detection Model

Viso.ai

The YOLO Family of Models The first YOLO model was introduced back in 2016 by a team of researchers, marking a significant advancement in object detection technology. They categorized these experiments as Bag of Freebies (BoF) and Bag of Specials (BoS). However, accuracy was poorer compared to two-stage models such as Faster RCNN.

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Computer Vision in Autonomous Vehicle Systems

Viso.ai

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.