DeepLearning | Aida Mohseni

Head Pose Estimation

Classification, CNN, ProjectsSeptember 21, 202474Views 0Likes 0Comments

This repository contains the implementation of a project aimed at head pose estimation using a custom Convolutional Neural Network (CNN). The project utilizes the Columbia Gaze dataset, involving steps from data preprocessing, creating synthetic labels for attention and distraction, to training a custom CNN model. This project aims to estimate head poses (attention and distraction)…

SVM Classification with CURE-SMOTE and K-fold Cross-validation

Classification, Data Augmentation, ProjectsSeptember 21, 202478Views 0Likes 0Comments

This code performs classification using a Support Vector Machine (SVM) algorithm combined with CURE-SMOTE oversampling. It is designed to handle imbalanced datasets and evaluate the model performance through k-fold cross-validation. GitHub: https://github.com/aidamohseni/SMOTE-Enhanced-SVM-Classification-with-Stratified-K-Fold

Handwriting Nastaliq Recognition

Classification, Neural Network, ProjectsSeptember 21, 202471Views 0Likes 0Comments

This is a project aimed at recognizing Nastaliq handwritten script, a form of Persian calligraphy. The project involves detecting writing items using contours and regrouping them based on geometric proximity. It uses a custom dataset of Nastaliq words and character combinations along with a CNN-BDLSTM hybrid model to recognize the text. GitHub: https://github.com/aidamohseni/Handwriting_Nastaliq_Recognition_BLSTM

Persian Handwriting Recognition using CNN-BLSTM Hybrid Model

Classification, Neural Network, ProjectsSeptember 20, 202479Views 0Likes 0Comments

This project aimed at recognizing Persian handwritten characters. The project employs a hybrid model integrating Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (BLSTM) networks to capture both spatial and sequential features essential for accurate recognition of Persian script. The model is evaluated using accuracy, precision, and recall metrics. The results are validated using…

Comparison of Synthesized and Natural Datasets in Neural Network Based Handwriting Solutions

PapersMarch 16, 202484Views 0Likes 0Comments

Using a large enough dataset is so important in a neural network based handwriting recognition solutions. On the other hand, producing natural datasets is so complicated and time-consuming. In this paper, we compare the effect of using synthesized datasets and natural datasets in state of the art neural network based solutions. For natural solution based…

Handwriting Recognition, a Comprehensive Review

PapersMarch 16, 202477Views 0Likes 0Comments

In this paper, we review classic handwriting recognition processes and controversial issues by details. In addition, since there are presented the state of the art approaches based on neural networks solutions, we review RNN approaches. Furthermore, as the database is an important factor in RNN based solutions, we survey the most important datasets for the…

The Rise of Generative AI: Revolutionizing Creative Industries

InnovationsFebruary 18, 202471Views 0Likes 0Comments

In recent years, the field of artificial intelligence (AI) has witnessed an unprecedented surge in innovation and application. Among the most groundbreaking developments is the advent of generative AI, a class of algorithms designed to create content. This technology is not just automating routine tasks; it's revolutionizing the way we think about creativity in industries…

Tag: DeepLearning

Head Pose Estimation

SVM Classification with CURE-SMOTE and K-fold Cross-validation

Handwriting Nastaliq Recognition

Persian Handwriting Recognition using CNN-BLSTM Hybrid Model

Comparison of Synthesized and Natural Datasets in Neural Network Based Handwriting Solutions

Handwriting Recognition, a Comprehensive Review

The Rise of Generative AI: Revolutionizing Creative Industries

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