Nitish is a computer science undergraduate with keen interest in the field of deep learning. He has done various projects related to deep learning and closely follows the new advancements taking place in the field.
This summary article is based on the paper 'SAT2LOD2: A SOFTWARE FOR AUTOMATED LOD-2 BUILDING RECONSTRUCTION
FROM SATELLITE-DERIVED ORTHOPHOTO AND DIGITAL SURFACE MODEL' and all...
This research summary is based on the paper 'DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation'
Please don't forget to join our ML Subreddit
GAN inversion...
This research summary is based on the paper 'CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs'
Please don't forget to join our ML Subreddit
GANs (Generative Adversarial...
This research summary is based on the papers 'Learning quantile functions without quantile crossing for distribution-free time series forecasting' and 'Multivariate quantile function forecaster'
Please...
This research summary is based on the paper 'Rethinking Portrait Matting with Privacy Preserving'
Please don't forget to join our ML Subreddit
Deep learning's effectiveness in...
This research summary is based on the paper 'Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing'
Please don't forget to join our ML Subreddit
Face...
This research summary article is based on the paper 'ALLIE: Active learning on large-scale imbalanced graphs'
Please don't forget to join our ML Subreddit
Social network...
This research summary article is based on the paper 'Parking Analytics Framework using Deep Learning'
Please don't forget to join our ML Subreddit
Artificial Intelligence and...
This research summary article is based on the research paper 'Global Tracking Transformers'.
Multi-object tracking aims to locate and track all objects in a video...
This research summary article is based on the paper 'ON THE UNREASONABLE EFFECTIVENESS OF FEATURE PROPAGATION IN LEARNING ON GRAPHS WITH MISSING NODE FEATURES'...
To learn visual representations, self-attention-based models, particularly vision transformers, offer an alternative to convolutional neural networks (CNNs). ViT breaks an image into a series...
