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Computer Vision in Robotics – An Autonomous Revolution

Viso.ai

One of the computer vision applications we are most excited about is the field of robotics. By marrying the disciplines of computer vision, natural language processing, mechanics, and physics, we are bound to see a frameshift change in the way we interact with, and are assisted by robot technology.

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Computer Vision in Robotics – An Autonomous Revolution

Viso.ai

One of the computer vision applications we are most excited about is the field of robotics. By marrying the disciplines of computer vision, natural language processing, mechanics, and physics, we are bound to see a frameshift change in the way we interact with, and are assisted by robot technology.

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Zero-Shot Learning: Unlocking the Power of AI Without Training Data

Pickl AI

By leveraging auxiliary information such as semantic attributes, ZSL enhances scalability, reduces data dependency, and improves generalisation. This innovative approach is transforming applications in computer vision, Natural Language Processing, healthcare, and more.

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Meet Swin3D++: An Enhanced AI Architecture based on Swin3D for Efficient Pretraining on Multi-Source 3D Point Clouds

Marktechpost

While deep learning methods have made significant strides in this domain, they often rely on large and diverse datasets to enhance feature learning, a strategy commonly employed in natural language processing and 2D vision. Check out the Paper and Github.

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Deep Learning Techniques for Autonomous Driving: An Overview

Marktechpost

These technologies have revolutionized computer vision, robotics, and natural language processing and played a pivotal role in the autonomous driving revolution. Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology.

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Convolutional Neural Networks: A Deep Dive (2024)

Viso.ai

In the following, we will explore Convolutional Neural Networks (CNNs), a key element in computer vision and image processing. Viso Suite enables the use of neural networks for computer vision with no code. Le propose architectures that balance accuracy and computational efficiency.

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Meet AnomalyGPT: A Novel IAD Approach Based on Large Vision-Language Models (LVLM) to Detect Industrial Anomalies

Marktechpost

On various Natural Language Processing (NLP) tasks, Large Language Models (LLMs) such as GPT-3.5 They optimize the LVLM using synthesized anomalous visual-textual data and incorporating IAD expertise. Direct training using IAD data, however, needs to be improved. Data scarcity is the first.