sohailahmedkhan/CLIPping-the-Deception

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Python
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MIT License
Created 9 months ago
Updated 7 months ago

sohailahmedkhan/CLIPping-the-Deception

sohailahmedkhan

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Code and pre-trained models for our paper "CLIPping the Deception: Adapting Vision-Language Models for Universal Deepfake Detection".

Flood-Detection-from-Images-using-Deep-Learning

Flood detection from images using deep learning. Deep learning library KERAS was employed and MobileNet architecture was fine-tuned for image classification task.

Jupyter Notebook

Phishing-Websites-Classification-using-Deep-Learning

A detailed comparison of performance scores achieved by Machine Learning and Deep Learning algorithms on 3 different Phishing datasets. 3 different feature selection and 2 different dimensionality reduction techniques are used for comparison.

Jupyter Notebook

Video-Transformer-for-Deepfake-Detection

This is the PyTorch implementation of our ACM Multimedia 2021 paper titled "Video Transformer for Deepfake Detection with Incremental Learning".

Jupyter Notebook

Sentence-Completion-using-Hidden-Markov-Models

The goal of this script is to implement three langauge models to perform sentence completion, i.e. given a sentence with a missing word to choose the correct one from a list of candidate words. The way to use a language model for this problem is to consider a possible candidate word for the sentence at a time and then ask the language model which version of the sentence is the most probable one.

Named-Entity-Recognition-using-Structured-Perceptron-Python

Named Entity Recogniser using Structured Perceptron in Python

Simple-SQL-XSS-Fuzzing-Tool-PYTHON-

Adversarial-Attack-on-Fine-Tuned-Flood-Detection-Model

Implementation of FGSM (Fast Gradient Sign Method) attack on fine-tuned MobileNet architecture trained for flood detection in images.

Jupyter Notebook

Searching-for-exotic-particles-in-high-energy-physics-using-classic-supervised-learning-algorithms

Supervised classification algorithms employed to explore and identify Higgs bosons from particle collisions, like the ones produced in the Large Hadron Collider. HIGGS dataset is used..

Efficient-Named-Entity-Recognizer-using-Structured-Perceptron-Viterbi-and-Beam-Search-Python

This script employs Dynamic Programming algorithms such as, Viterbi Search and Beam Search, to accelerate the process of training Multilayer Perceptron

Deepfake-Detection

Deepfake Detection: Analysing Model Generalisation Across Architectures, Datasets, and Pre-Training Paradigms

Jupyter Notebook