Code for experiments for "ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy"
"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 structure-based, alignment-free embedding approach for proteins. Can be used as input to machine learning algorithms.
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
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.
A Python implementation of complex invariants by Flusser et al.
Transform-Invariant Non-Negative Matrix Factorization
Demonstration of sift algorithm to track objects and observing the effect of each parameter on performance.
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.
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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
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