Viso.ai

OCTOBER 9, 2024

Enterprise computer vision pipeline with Viso Suite We provide an overview of Emotion AI technology, trends, examples, and applications: What is Emotion AI? How does visual AI Emotion Recognition work? Facial Emotion Recognition Datasets What Emotions Can AI Detect? Get a personalized demo for your organization.

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Convolutional Neural Networks Neural Network Computer Vision Emotion AI 98

Viso.ai

NOVEMBER 27, 2024

Object detection is a computer vision task that uses neural networks to localize and classify objects in images. Multiple machine-learning algorithms are used for object detection, one of which is convolutional neural networks (CNNs). To learn more, book a demo with our team.

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Explainability Convolutional Neural Networks Neural Network Computer Vision 52

Heartbeat

MAY 22, 2023

It gives the computer the ability to observe and learn from visual data just like humans. In this process, the computer derives meaningful information from digital images, videos etc. and applies this learning tosolving problems.

Computer Vision 52

Computer Vision Convolutional Neural Networks Emotion AI Deep Learning 52

Viso.ai

NOVEMBER 11, 2024

We’ll explore the key AI technologies that enable them, examine real-world applications, and a hands-on tutorial for obstacle detection. About us : Viso Suite is the end-to-end platform for building, deploying, and scaling visual AI. Following are some of those algorithms.

Computer Vision 52

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Viso.ai

MAY 20, 2023

It requires several times cheaper hardware than other neural networks and can be trained much faster on small datasets without any pre-trained weights. Most algorithms use a convolutional neural network (CNN) to extract features from the image to predict the probability of learned classes.

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Algorithm Computer Vision Deep Learning Neural Network 52

Unite.AI

AUGUST 8, 2023

The Technologies Behind Generative Models Generative models owe their existence to deep neural networks, sophisticated structures designed to mimic the human brain's functionality. By capturing and processing multifaceted variations in data, these networks serve as the backbone of numerous generative models.

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