Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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Viso.ai

NOVEMBER 4, 2024

Computer Vision Model for Solar Prediction The researchers based their solution on computer vision, specifically deep Convolutional neural networks (CNNs) for object localization and identification. Lastly, the model in recurrent neural network techniques (e.g.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

Viso.ai

MAY 20, 2023

The YOLOv7 algorithm is making big waves in the computer vision and machine learning communities. In this article, we will provide the basics of how YOLOv7 works and what makes it the best object detector algorithm available today. The original YOLO object detector was first released in 2016. higher AP (average precision).

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Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. Popular image recognition algorithms include ResNet , VGG , YOLOv3 , and YOLOv7.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Viso.ai

DECEMBER 18, 2023

YOLOv8 is the newest model in the YOLO algorithm series – the most well-known family of object detection and classification models in the Computer Vision (CV) field. In this article, we’ll discuss: The evolution of the YOLO algorithms Improvements and enhancements in YOLOv8 Implementation details and tips Applications About us: Viso.ai

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Algorithm 52

Viso.ai

FEBRUARY 19, 2024

Criminal Activity Detection In criminal cases, CV algorithms should first recognize the environment and the setting. The global look of the scene will help the algorithm capture details, including the color and shape of vehicles, license plates, signboards, storefronts, etc.

Computer Vision 52

Computer Vision Deep Learning Convolutional Neural Networks Neural Network 52

How to Learn Machine Learning

MAY 14, 2023

Mathematics is crucial because machine learning algorithms are built on concepts such as linear algebra, calculus, probability, and statistics. Familiarity with these subjects will enable you to understand and implement machine learning algorithms more effectively. Publisher) Buy on Amazon 5.

Machine Learning 52

Machine Learning Convolutional Neural Networks Natural Language Processing Deep Learning 52

Viso.ai

OCTOBER 15, 2024

YOLO (You Only Look Once) is a state-of-the-art (SOTA) object-detection algorithm introduced as a research paper by J. In the field of real-time object identification, YOLOv11 architecture is an advancement over its predecessor, the Region-based Convolutional Neural Network (R-CNN). Redmon, et al.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Python 52

Heartbeat

MAY 22, 2023

Genetic algorithms [ 1 ] are one way to detect faces in a digital image, followed by the Eigenface technique to verify the fitness of the region of interest. 2020 ) can be integrated to add greater weight to the core features. It is then re-trained to derive patterns of facial expressions using negative and positive values.

Computer Vision 52

Computer Vision Convolutional Neural Networks Emotion AI Deep Learning 52

Viso.ai

FEBRUARY 27, 2024

Since its inception in 2015, the YOLO (You Only Look Once) object-detection algorithm has been closely followed by tech enthusiasts, data scientists, ML engineers, and more, gaining a massive following due to its open-source nature and community contributions. Girshick, and A. The model achieved 43.5 mAP at 65 FPS on the COCO dataset.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Python 52

Viso.ai

OCTOBER 7, 2024

This is an iterative approach where the user interacts with a machine-learning algorithm such as a computer vision (CV) system and provides feedback on its outputs. This iterative approach involves user interaction with a machine-learning algorithm, such as a computer vision (CV) system, providing feedback on its outputs.

Computer Vision 52

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Viso.ai

MAY 6, 2024

The latest version is Kinetics 700-2020, which contains over 700 human action classes from up to 650,000 video clips. Spatio-Temporal Action Recognition – Model Architectures and Algorithms Due to technological limitations, initial research focused separately on spatial and temporal features. Successive releases (e.g.,

Computer Vision 52

Computer Vision Deep Learning Neural Network Convolutional Neural Networks 52

Viso.ai

JUNE 4, 2024

Point Cloud Processing Methods Computer vision algorithms provide point cloud processing functionalities that include: point cloud registration, shape fitting to 3-D point clouds , and the ability to read, write, store, display, and compare point clouds. 2020) proposed a generalization of discrete CNNs. Boulch et al.

Computer Vision 52

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 52

Marktechpost

JULY 24, 2023

The EC’s 10-day wind-field forecasts were corrected for rolling bias in real-time from December 2020 to November 2021 throughout all four seasons. This model predicts rainfall for the full satellite area using convolutional neural networks’ spatial invariance, even if radar data is only available for a smaller area.

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network ML 52

Lexalytics

APRIL 5, 2021

This would change in 1986 with the publication of “Parallel Distributed Processing” [ 6 ], which included a description of the backpropagation algorithm [ 7 ]. Note that Geoff Hinton was a co-author on this paper: his interest in neural networks was finally vindicated. The figure above shows a back-propagation network.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

AWS Machine Learning Blog

FEBRUARY 10, 2023

For a given frame, our features are inspired by the 2020 Big Data Bowl Kaggle Zoo solution ( Gordeev et al. ): we construct an image for each time step with the defensive players at the rows and offensive players at the columns. This is achieved through the Guided GradCAM algorithm ( Ramprasaath et al. ). probability.

Computer Vision 73

Computer Vision Machine Learning ML Convolutional Neural Networks 73

Snorkel AI

MARCH 1, 2023

This model debuted in June 2020, but remained a tool for researchers and ML practitioners until its creator, OpenAI, debuted a consumer-friendly chat interface in November 2022. It is based on GPT and uses machine learning algorithms to generate code suggestions as developers write. Attention Is All You Need Vaswani et al.

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BERT Natural Language Processing Large Language Models Neural Network 83

Google Research AI blog

JANUARY 18, 2023

Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics. The neural network perceives an image, and generates a sequence of tokens for each object, which correspond to bounding boxes and class labels.

Computer Vision 132

Computer Vision Auto-classification Large Language Models Neural Network 132

ML Review

DECEMBER 16, 2019

Source: HyperE Traditional embedding algorithms place the learned vectors in Euclidean “flat” space of possibly high dimensionality (50–200) where distance between two vectors can be expressed with Euclidean geometry. In contrast, hyperbolic algorithms employ Poincare balls and hyperbolic space. Thank you for reading!

Machine Learning 52

Machine Learning Neural Network Explainability Convolutional Neural Networks 52

Unite.AI

AUGUST 8, 2023

These algorithms take input data, such as a text or an image, and pair it with a target output, like a word translation or medical diagnosis. GPT-3, launched in May 2020 had 96 layers, 96 attention heads, and a massive parameter count of 175 billion. Discriminative models are what most people encounter in daily life.

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