Remove Data Scarcity Remove Deep Learning Remove Natural Language Processing
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Deep Learning Techniques for Autonomous Driving: An Overview

Marktechpost

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

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

Marktechpost

Point clouds serve as a prevalent representation of 3D data, with the extraction of point-wise features being crucial for various tasks related to 3D understanding. However, the scarcity and limited annotation of 3D data present significant challenges for the development and impact of 3D pretraining.

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What is Transfer Learning in Deep Learning? [Examples & Application]

Pickl AI

Transfer Learning in Deep Learning: A Brief Overview Collecting large volumes of data, filtering it and then interpreting is a challenging task. What if we say that you have the option of using a pre-trained model that works as a framework for data training? Yes, Transfer Learning is the answer to it.

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Award-Winning Breakthroughs at NeurIPS 2023: A Focus on Language Model Innovations

Topbots

A key finding is that for a fixed compute budget, training with up to four epochs of repeated data shows negligible differences in loss compared to training with unique data. The paper also explores alternative strategies to mitigate data scarcity.

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Unlocking Deep Learning’s Potential with Multi-Task Learning

Pickl AI

Multi-Task Learning Deep Learning is a towering pillar in the vast landscape of artificial intelligence, revolutionising various domains with remarkable capabilities. Deep Learning algorithms have become integral to modern technology, from image recognition to Natural Language Processing.

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Achieving accurate image segmentation with limited data: strategies and techniques

deepsense.ai

Harnessing the power of deep learning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle – the limited availability of training data. Over the years, various successful deep learning architectures have been developed for this task, such as U-Net or SegFormer.

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Computer Vision in Robotics – An Autonomous Revolution

Viso.ai

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. Processing this data also demands significant computational resources, especially for deep learning models.