Mlearning.ai

APRIL 8, 2023

2003) “ Support-vector networks ” by Cortes and Vapnik (1995) Significant people : David Blei Corinna Cortes Vladimir Vapnik 4. Deep Learning (Late 2000s — early 2010s) With the evolution of needing to solve more complex and non-linear tasks, The human understanding of how to model for machine learning evolved.

NLP 98

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Heartbeat

MAY 22, 2023

2020 ) can be integrated to add greater weight to the core features. Schematic diagram of the overall framework of Emotion Recognition System [ Source ] The models that are used for AI emotion recognition can be based on linear models like Support Vector Machines (SVMs) or non-linear models like Convolutional Neural Networks (CNNs).

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Heartbeat

JUNE 6, 2023

GCNs use a combination of graph-based representations and convolutional neural networks to analyze large amounts of textual data. A GCN consists of multiple layers, each of which applies a graph convolution operation to the input graph. References Paperwithcode | Graph Convolutional Network Kai, S.,

NLP 59

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Marktechpost

JULY 24, 2023

Many studies have been motivated to explore hidden hierarchical patterns in the large volume of weather datasets for weather forecasting due to the recent development of deep learning techniques, the widespread availability of massive weather observation data, and the advent of information and computer technology.

Deep Learning 52

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Unite.AI

OCTOBER 10, 2024

JPEG-DL Instead, the new work , titled JPEG Inspired Deep Learning , offers a much simpler architecture, which can even be imposed upon existing models. Data and Tests JPEG-DL was evaluated against transformer-based architectures and convolutional neural networks (CNNs).

Neural Network 162

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Viso.ai

DECEMBER 3, 2023

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% ).

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

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. No 2020 Jul iGPT The transformer model, originally developed for NLP, can also be used for image pre-training.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Viso.ai

MAY 6, 2024

And when it comes to technologies based on deep learning , that means vast and varied data sets to train on. The latest version is Kinetics 700-2020, which contains over 700 human action classes from up to 650,000 video clips. An easy-to-understand guide to Deep Reinforcement Learning.

Computer Vision 52

Computer Vision Deep Learning Neural Network Convolutional Neural Networks 52

Viso.ai

OCTOBER 7, 2024

Roles of Humans in the Machine Learning Cycle The recent developments in deep learning models have led to AI’s irreplaceable role in many fields. Consequently, human-in-the-loop machine learning is gaining increasing importance. 2020)): An improvement from 0.645 accuracy to 0.846 with the framework used.

Computer Vision 52

Computer Vision Machine Learning Deep Learning Convolutional Neural Networks 52

NVIDIA

OCTOBER 4, 2023

Harnessing the raw power of NVIDIA GPUs and aided by a network of thousands of cameras dotting the Californian landscape, DigitalPath has refined a convolutional neural network to spot signs of fire in real time. a short drive from the town of Paradise, where the state’s deadliest wildfire killed 85 people in 2018.

Convolutional Neural Networks 86

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Viso.ai

JUNE 4, 2024

Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. Many of these methods utilize deep learning and Convolutional Neural Networks (CNNs) to create point cloud processing.

Computer Vision 52

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 52

Viso.ai

FEBRUARY 19, 2024

applied deep learning R-CNN for document classification and clustering. To overcome this IP concern – researchers have applied a Convolutional Neural Network (CNN) to detect plagiarized text and images as well as problematic deepfakes on the internet. Handwritten content detection – source. How is this done?

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Computer Vision Deep Learning Convolutional Neural Networks Neural Network 52

Mlearning.ai

FEBRUARY 2, 2023

In this article, I show how a Convolutional Neural Network can be used to predict a person's age based on the person's ECG Attia et al 2019 [1], showed that a person's age could be predicted from an ECG using convolutional neural networks (CNN). Data Min Knowl Disc 34 , 1936–1962 (2020).

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning Explainable AI 52

Lexalytics

APRIL 5, 2021

They were not wrong: the results they found about the limitations of perceptrons still apply even to the more sophisticated deep-learning networks of today. This book effectively killed off interest in neural networks at that time, and Rosenblatt, who died shortly thereafter in a boating accident, was unable to defend his ideas.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Viso.ai

MAY 20, 2023

Most algorithms use a convolutional neural network (CNN) to extract features from the image to predict the probability of learned classes. As a result, YOLOv7 requires several times cheaper computing hardware than other deep learning models. in 2018 YOLOv4 model, released by Bochkovskiy et al.

Algorithm 52

Algorithm Computer Vision Deep Learning Neural Network 52

Viso.ai

DECEMBER 18, 2023

Viso Suite is the end-to-end, No-Code Computer Vision Platform for Businesses – Learn more What is YOLO You Only Look Once (YOLO) is an object-detection algorithm introduced in 2015 in a research paper by Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi. The essential mechanics of an object detection model – source.

Computer Vision 52

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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. Haibo Ding is a senior applied scientist at Amazon Machine Learning Solutions Lab.

Computer Vision 69

Computer Vision Machine Learning ML Convolutional Neural Networks 69

Unite.AI

AUGUST 8, 2023

Instead of complex and sequential architectures like Recurrent Neural Networks (RNNs) or Convolutional Neural Networks (CNNs), the Transformer model introduced the concept of attention, which essentially meant focusing on different parts of the input text depending on the context.

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