article thumbnail

Digging Into Various Deep Learning Models

Pickl AI

Convolutional Neural Networks (CNNs) Convolutional Neural Networks ( CNNs ) are specialised Deep Learning models that process and analyse visual data. Understanding Convolution and Pooling Layers CNNs rely on two key operations: convolution and pooling.

article thumbnail

Unveiling the GaoFen-7 Building Dataset: A New Horizon in Satellite-Based Urban and Rural Building Extraction

Marktechpost

In urban development and environmental studies, accurate and efficient building data extraction from satellite imagery is a cornerstone for myriad applications. These advanced methods grapple with a common Achilles’ heel: the dire need for extensive, high-quality training data reflective of real-world diversity.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Leveraging user-generated social media content with text-mining examples

IBM Journey to AI blog

Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data. It weighs down frequently occurring words and emphasizes rarer, more informative terms. positive, negative or neutral).

article thumbnail

Deep Learning based Table Extraction using Visual NLP 1/2

John Snow Labs

Results for Image Table Detection using Visual NLP Introduction: Why is Table Extraction so crucial? Table recognition is a crucial aspect of OCR because it allows for structured data extraction from unstructured sources. Tables often contain valuable information organized systematically.

article thumbnail

Most Important Deep Learning Interview Questions For You

Pickl AI

Unlike traditional Machine Learning, Deep Learning models automatically discover features without human intervention, making them highly effective in handling unstructured data like images, text, and audio. Key Concepts At the core of Deep Learning are neural networks composed of layers of interconnected nodes or neurons.

article thumbnail

ML and NLP Research Highlights of 2020

Sebastian Ruder

2020 ), and to be vulnerable to model and data extraction attacks ( Krishna et al.,  While Transformers have achieved large success in NLP, they were—up until recently—less successful in computer vision where convolutional neural networks (CNNs) still reigned supreme. 2020 ; Wallace et al.,

NLP 52
article thumbnail

Large Language Models in Pathology Diagnosis

John Snow Labs

For instance, convolutional neural networks (CNNs) are used in tandem with transformer-based models to interpret histopathology slides alongside corresponding reports, providing a holistic view of patient data.