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Found 17 papers, 4 papers with code
ArabianGPT: Native Arabic GPT-based Large Language Model
The predominance of English and Latin-based large language models (LLMs) has led to a notable deficit in native Arabic LLMs.
Prediction of Arabic Legal Rulings using Large Language Models
Furthermore, we show that all scores except human evaluation are inconsistent and unreliable for assessing the performance of large language models on court decision predictions.
License Plate Super-Resolution Using Diffusion Models
By training this model using a curated dataset of Saudi license plates, both in low and high resolutions, we discovered the diffusion model's superior efficacy.
Early Detection of Red Palm Weevil Infestations using Deep Learning Classification of Acoustic Signals
The third step involves the application of different Deep Learning (DL) techniques to classify resulting images into two classes: infested and not infested.
ERA*: Enhanced Relaxed A* algorithm for Solving the Shortest Path Problem in Regular Grid Maps
This paper introduces a novel algorithm for solving the point-to-point shortest path problem in a static regular 8-neighbor connectivity (G8) grid.
Interpretation of immunofluorescence slides by deep learning techniques: anti-nuclear antibodies case study
Nowadays, diseases are increasing in numbers and severity by the hour.
Humans are Still Better than ChatGPT: Case of the IEEEXtreme Competition
Since the release of ChatGPT, numerous studies have highlighted the remarkable performance of ChatGPT, which often rivals or even surpasses human capabilities in various tasks and domains.
TAU: A Framework for Video-Based Traffic Analytics Leveraging Artificial Intelligence and Unmanned Aerial Systems
Fifth, TAU has a fully independent algorithm for crossroad arbitration based on the data gathered from the different zones surrounding it.
Parking Analytics Framework using Deep Learning
With the number of vehicles continuously increasing, parking monitoring and analysis are becoming a substantial feature of modern cities.
Securing the Classification of COVID-19 in Chest X-ray Images: A Privacy-Preserving Deep Learning Approach
In this paper, we propose privacy-preserving deep learning (PPDL)-based approach to secure the classification of Chest X-ray images.
Deep-Learning-based Automated Palm Tree Counting and Geolocation in Large Farms from Aerial Geotagged Images
In this paper, we propose a deep learning framework for the automated counting and geolocation of palm trees from aerial images using convolutional neural networks.
DriftNet: Aggressive Driving Behavior Classification using 3D EfficientNet Architecture
In this paper, we propose a new anomaly detection framework applied to the detection of aggressive driving behavior.
AI-based Pilgrim Detection using Convolutional Neural Networks
Then, we develop two convolutional neural networks based on YOLOv3 and Faster-RCNN for the detection of Pilgrims.
Activity Monitoring of Islamic Prayer (Salat) Postures using Deep Learning
However, for several people, these postures are not correctly performed, due to being new to Salat or even having learned prayers in an incorrect manner.
Aerial Images Processing for Car Detection using Convolutional Neural Networks: Comparison between Faster R-CNN and YoloV3
In this paper, we address the problem of car detection from aerial images using Convolutional Neural Networks (CNN).
Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3
In this paper, we investigate the performance of two state-of-the-art CNN algorithms, namely Faster R-CNN and YOLOv3, in the context of car detection from aerial images.
Building a Learning Database for the Neural Network Retrieval of Sea Surface Salinity from SMOS Brightness Temperatures
The present study focuses on the choice of the learning database and demonstrates that a judicious distribution of the geophysical parameters allows to markedly reduce the systematic regional biases of the retrieved SSS, which are due to the high noise on the TBs.
