Deep Learning

Neural Radiance Fields (NeRFs) are a deep learning technique that is revolutionizing the way we represent and interact with 3D scenes. Discover the core concepts

GoogLeNet is an Image Classification model that is made by stacking Inception Modules. Released in 2014, it surpassed previous benchmarks.

Spatio-Temporal Action Recognition encompasses the complex task of understanding actions in videos, including what action is happening and when and where it occurs.

MobileNet, introduced in 2017 by a team of researchers at Google, is a Deep Learning model for Smartphones, IoT, and embedded devices.

AlexNet is a Image Classification model released in 2012 and the first model to use CNN based Deep Neural Network.

U-Net is an image segmentation model that features a U-shaped architecture, comprising two main parts: an encoder and decoder.

RetinaNet is a single-stage object detector that uses Focal Loss and two task-specific sub-networks for object detection.

Explore the decision tree algorithm and enhance your Python skills with step-by-step instructions in this comprehensive guide.

Pandas is a free and open-source Python library for data manipulation and analysis. It excels at working with structured data.

Vision Language Models merge the capabilities of natural language processing (NLP) and computer vision for applications across industries.

Model drift can degrade a model's performance. Learn about the differences between concept drift vs data drift and mitigation strategies.

Multispectral imaging captures light across a broad range of spectral bands, extending beyond what the human eye can see