Supervised Learning has been dominant for years, but its reliance on labeled data—a costly and time-consuming resource—creates challenges, especially in areas like medical imaging. On the other hand, ...
The Annotated NeRF – Training on Custom Dataset from Scratch in Pytorch
In recent years, the field of 3D from multi-view has become one of the most popular topics in computer vision conferences, with a high number of submitted papers each year. A groundbreaking paper in ...
LightRAG: Simple and Fast Alternative to GraphRAG for Legal Doc Analysis
LightRAG is an innovative approach based on GraphRAG that combines the attributes of Knowledge Graphs with embedding-based retrieval systems, making it fast as well as performant, achieving SOTA ...
NVIDIA AI Summit 2024 – India Overview
The NVIDIA AI Summit 2024, held from October 23 to 25 at the Jio World Convention Centre in Mumbai, marked a significant milestone in India's journey toward becoming a global leader in artificial ...
Introduction to Speech to Speech: Most Efficient Form of NLP
We often take out our phones and say, “Hey Siri, play Perfect by Ed Sheeran” or “Ok Google, set an alarm at 7.30 in the morning.” And the work is done on the flow by our phones! But have you ever ...
Training 3D U-Net for Brain Tumor Segmentation (BraTS2023-GLI) Challenge
3D U-Net, an efficient paradigm in medical segmentation, excels at analyzing 3D volumetric data, allowing it to capture a holistic view of brain scans. In many parts of the world, ...
