hasanar1f

AngryBirds

This is a PLAYABLE simple angry-bird-like game written on C using i-graphics tool \m/

CPP-Compiler-using-flex-bison

Distance-Vector-Routing-DVR-Protocol---Simulation

using java socket.

GhostBuster.Ai

Gun---OpenGL-graphics-project

HiRED

HiRED strategically drops visual tokens in the image encoding stage to improve inference efficiency for High-Resolution Vision-Language Models (e.g., LLaVA-Next) under a fixed token budget.

Implement-AES-encryption

Lines-Of-Action

LLaVA

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

Ray-Tracing-

hasanar1f/AngryBirds

This is a PLAYABLE simple angry-bird-like game written on C using i-graphics tool \m/

hasanar1f/Lines-Of-Action

hasanar1f/Ray-Tracing-

hasanar1f/CPP-Compiler-using-flex-bison

hasanar1f/Pinterest

hasanar1f/Police-department-automation

hasanar1f/LLaVA

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

hasanar1f/Cross-Site-Scripting-XSS-Attack

Cross-site scripting (XSS) is a type of vulnerability commonly found in web applications. This vulnerability makes it possible for attackers to inject malicious code (e.g. JavaScript programs) into victim’s web browser. Using this malicious code, attackers can steal a victim’s credentials, such as session cookies. The access control policies (i.e., the same origin policy) employed by browsers to protect those credentials can be bypassed by exploiting XSS vulnerabilities.

hasanar1f/Dictionary-and-Known-Password-Attack-tool-using-cpp

hasanar1f/Fuse-Project-1

hasanar1f/GitFazz

showcasing my github ;)

hasanar1f/Hidden-Markov-Models-Viterbi-and-the-Baum-Welch-algorithm.

The aim is to model with a Hidden Markov Model (HMM), and implement the Viterbi and the Baum-Welch algorithm

hasanar1f/implementation-of-convolutional-neural-network-for-an-image-classification-task-from-Scratch

1. Convolution layer: there will be four (hyper)parameters: the number of output channels, filter dimension, stride, padding. 2. Activation layer: implement an element-wise ReLU. 3. Max-pooling layer: there will be two parameters: filter dimension, stride. 4. Fully-connected layer: a dense layer. There will be one parameter: output dimension. 5. Flattening layer: it will convert a (series of) convolutional filter maps to a column vector. 6. Softmax layer: it will convert final layer projections to normalized probabilities.

hasanar1f/Implementation-of-Perceptron-and-its-variants

Implement 2-class classifiers using – Basic perceptron algorithm – Reward and punishment (RP) algorithm – Pocket algorithm

hasanar1f/LLaVA-NeXT

hasanar1f/LLFI-upgrade

LLFI is an LLVM based fault injection tool, that injects faults into the LLVM IR of the application source code. The faults can be injected into specific program points, and the effect can be easily tracked back to the source code. Please refer to the paper below. NOTE: If you publish a paper using LLFI, please add it to PaperLLFI.bib

hasanar1f/Logistic-Regression-and-AdaBoost-for-Classification

In ensemble learning, we combine decisions from multiple weak learners to solve a classification problem. Here, I will implement a Logistic Regression (LR) classifier and use it within AdaBoost algorithm.

hasanar1f/LUDO-with-JavaFX

This a conventional LUDO game code written in java and javaFX.

hasanar1f/My-leetcode-Solve

targeting to solve leetcode problems on regular basis and gather them here ;-)

hasanar1f/my-portfolio-website

hasanar1f/OpenGL-Graphics-project-in-c

hasanar1f/Operating-System-coding

hasanar1f/Rasterization-based-computer-graphics-Pipeline

4 stages of the pipeline. 1. Stage 1: modeling transformation 2. Stage 2: view transformation 3. Stage 3: projection transformation 4. Stage 4: clipping & scan conversion using Z-buffer algorithm

hasanar1f/Satellite-Images-2-Map-Coloring

hasanar1f/ShapeWorks

ShapeWorks

hasanar1f/Smartphone-Price-Range-Classification

hasanar1f/Stat-CS-5525-Data-Analytics-I

hasanar1f/Statistical-Shape-Modeliing-with-Scalismo

hasanar1f/Template-Matching-in-a-video-using-exhaustive--logarithmic-and-hierarchical-search-techniques-

It tracks a reference object in a video file. The output will be another video file output.mov showing the location of the reference object using bounding boxes in each frame.

hasanar1f/transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.