Code for experiments for "ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy"

A structure-based, alignment-free embedding approach for proteins. Can be used as input to machine learning algorithms.

"Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning" by Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah (CVPR 2021)

A Python and OpenCV implementation of Image Stitching using Brute Force Matcher and ORB feature descriptures.

Repository for the code of the paper "Neural Networks Regularization Through Class-wise Invariant Representation Learning".

Towards a rotationally invariant convolutional layer

Perception Modelling by Invariant Representation of Deep Learning for Automated Structural Diagnostic in Aircraft Maintenance: A Study Case using DeepSHM

Carloni, G., Tsaftaris, S. A., & Colantonio, S. (2024). CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning @ MICCAI 2024 UNSURE Workshop

Demonstration of sift algorithm to track objects and observing the effect of each parameter on performance.

Transform-Invariant Non-Negative Matrix Factorization

A Python implementation of complex invariants by Flusser et al.

Computer Vision project for object detection. Grocery items are detected on a store shelf from single model images using local invariant features and the Generalized Hough transform.

An improved and tested code to produce Hu's Invariant moments for any Image/ Audio signals. Hu's Invariant Moments are One of the Best Feature Extraction Techniques for Further Analysis.

Adaptive color-based particle filtering for object tracking in video sequences.

Pattern recognition image classification using moment invariants.

This is the final project for Udacity A/B Testing provided by Google. In this project, We implement a few statistical powers to make our data-driven solution that can bring impact to business