Author: Mahmoud Ghorbel

Mahmoud Ghorbel
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Mahmoud is a PhD researcher in machine learning. He also holds a bachelor's degree in physical science and a master's degree in telecommunications and networking systems. His current areas of research concern computer vision, stock market prediction and deep learning. He produced several scientific articles about person re- identification and the study of the robustness and stability of deep networks.

Latest Computer Vision Research Proposes A Novel Plug-And-Play Module For Vision Transformer Architectures That Augments Its Ability To Handle Higher Resolution Input Images With...

AI Paper Summary
Herbarium sheets offer a singular perspective on the botanical world's diversity and history. They are, therefore, a crucial source of information for botanical study....

Researchers at Imperial College London Developed Deep Learning-Based Choice Models Under Feature-Free and Feature-Based Settings of Choice Modeling

Deep Learning
Choice modeling tries to simulate a person's or a group's decision-making process using preferences disclosed or explicitly stated in a given setting or circumstances....

Researchers at Ludwig-Maximilian University Propose Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models

AI Paper Summary
The development of generative models for text-to-image synthesis has advanced significantly. Recently, these models have had wide success in the application in the field...

Researchers Develop DL-GuesS: A Deep Learning and Sentiment Analysis-Based Framework For Cryptocurrency Price Prediction

AI Paper Summary
A cryptocurrency is a string of encrypted data representing a currency unit. It has been hugely successful since money transfers are cheaper and faster,...

Researchers From China Introduce A Re-Attention Method Called The Token Refinement Transformer (TRT) That Captures Object Level Semantics For The Task of WSOL

AI Paper Summary
Object localization, a fundamental computer vision task, is crucial to many computer vision-based applications. While supervised approaches use manual location labels to learn to...

Researchers Propose Easter2.0, a Novel Convolutional Neural Network CNN-Based Architecture for the Task of End-to-End Handwritten Text Line Recognition that Utilizes Only 1D Convolutions

AI Paper Summary
The capability of a computer or device to read handwriting from sources such as printed physical documents, images, and other devices as input or...

Researchers From Italy Propose A New AI Method Focussed on Unsupervised Feature Learning for MER (Multimodal Emotion Recognition)

AI Paper Summary
The use of technology to assist humans or robots in recognizing emotions is a relatively new field of study and still challenging since perception...

In A Latest Computer Vision Research, A Research Team Proposes A Novel Data Augmentation Technique Called ‘TokenMix’ To Improve The Performance of Vision Transformers

AI Paper Summary
Data augmentation is creating additional data points from current data to increase the dataset size artificially. It is used to improve the performance and...

Researchers From China Propose The Artificial Intelligence-Based Hybrid Attention Network Model (BA-CNN) To Implement An Aircraft Recognition Algorithm

AI Paper Summary
Aircraft classification is a widely studied task. It is considered a fine-grained image classification (FGVC) since all images belong to the same class. Because...

AI Researchers From University of Hong Kong Propose Unified Python Framework, Named Face Feature Rectification Network (FFR-Net), For Masked And Mask-Free Face Recognition

AI Paper Summary
Facial recognition is an area of research that has been extensively studied in recent years. It has been very successful and has achieved satisfactory...

Researchers From China Propose A Novel Attention High-Order Deep Network ‘AHoNet’ For Breast Cancer Histopathological Image Classification

AI Paper Summary
Breast cancer is the most common and deadliest cancer for women. It is therefore essential to detect it early to reduce the risk of...

AI Researchers From China Designed An Image Classification Algorithm, FGVC, Based On Self-Attention Feature Fusion And Graph-Propagation

AI Paper Summary
Analyzing images from subordinate categories such as airplane models or bird species is fine-grained image classification's main goal (FGVC) goal. Due to the fine-grained...
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