Viso.ai

DECEMBER 20, 2023

Get a demo for your organization. However, unsupervised learning has its own advantages, such as being more resistant to overfitting (the big challenge of Convolutional Neural Networks ) and better able to learn from complex big data, such as customer data or behavioral data without an inherent structure. About us: Viso.ai

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Viso.ai

DECEMBER 22, 2023

The Segment Anything Model Technical Backbone: Convolutional, Generative Networks, and More Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) play a foundational role in the capabilities of SAM. This is essential for its high accuracy and efficiency in image segmentation.

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Viso.ai

DECEMBER 6, 2023

Get a demo here. State of Computer Vision Tasks in 2024 The field of computer vision today involves advanced AI algorithms and architectures, such as convolutional neural networks (CNNs) and vision transformers ( ViTs ), to process, analyze, and extract relevant patterns from visual data.

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Viso.ai

JANUARY 4, 2024

Get a demo. Unlike simple segmentation that might just separate foreground from background, semantic segmentation categorizes all pixels in an image into predefined categories. At its core, Semantic Segmentation is driven by deep learning models , particularly Convolutional Neural Networks (CNNs) , acting as an encoder and decoder.

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Viso.ai

FEBRUARY 19, 2024

To learn more, book a demo with the Viso team. CV algorithms can accurately categorize documents by analyzing document characteristics including structures, layout, and formatting. To get started using computer vision for solutions in the world of law and regulation, book a demo with us.

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Viso.ai

DECEMBER 18, 2023

Get a demo. YOLO’s architecture was a significant revolution in the real-time object detection space, surpassing its predecessor – the Region-based Convolutional Neural Network (R-CNN). The neck merges these feature maps using path aggregation blocks like the Feature Pyramid Network (FPN).

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Viso.ai

JANUARY 16, 2024

Get a demo here. The AI community categorizes N-shot approaches into few, one, and zero-shot learning. Matching Networks: The algorithm computes embeddings using a support set, and one-shot learns by classifying the query data sample based on which support set embedding is closest to the query embedding – source.

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Viso.ai

MARCH 6, 2024

To learn more, book a demo for your company. During the segmentation process, each RGB pixel in an image is categorized as having a color in a specific range or not. Deep Learning-Based Registration: It applies convolutional neural networks (CNNs) to learn the transformation directly from image pairs.

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Viso.ai

MARCH 26, 2024

Learn more by booking a demo. Attention Mechanisms in Deep Learning Attention mechanisms are helping reimagine both convolutional neural networks ( CNNs ) and sequence models. By integrating attention with CNNs, the networks can selectively focus on certain areas within an image or video frame.

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Viso.ai

JULY 9, 2024

Book a demo to learn more. As the name suggests, this technique involves transferring the learnings of one trained machine learning model to another, in the form of neural network weights. VGG16 has a CNN ( Convolutional Neural Network ) based architecture that has 16 layers. What is Transfer Learning?

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Viso.ai

MARCH 7, 2023

Get a demo for your company. Explanation and Definition of Autoencoders Autoencoders are neural networks that can learn to compress and reconstruct input data, such as images, using a hidden layer of neurons. About us: Viso.ai powers the leading end-to-end Computer Vision Platform Viso Suite. What is an Autoencoder?

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Viso.ai

JUNE 24, 2024

To learn more, book a demo with our team. We can categorize the types of AI for the blind and their functions. These models usually use a classification algorithm like a Convolutional Neural Network (CNN) or a multimodal architecture. For a demo inference, you can try the Colab notebook or the HuggingFace space.

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