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Found 8 papers, 2 papers with code
ArabicaQA: A Comprehensive Dataset for Arabic Question Answering
In conclusion, ArabicaQA, AraDPR, and the benchmarking of LLMs in Arabic question answering offer significant advancements in the field of Arabic NLP.
Advancements and Challenges in Arabic Optical Character Recognition: A Comprehensive Survey
A thorough analysis is conducted on prevailing techniques utilized throughout the OCR process, with a dedicated effort to discern the most efficacious approaches that demonstrate enhanced outcomes.
Optical Character Recognition
Optical Character Recognition (OCR)
Deep learning for table detection and structure recognition: A survey
The goals of this survey are to provide a profound comprehension of the major developments in the field of Table Detection, offer insight into the different methodologies, and provide a systematic taxonomy of the different approaches.
Detection of False-Reading Attacks in the AMI Net-Metering System
Based on the data analysis, we propose a general multi-data-source deep hybrid learning-based detector to identify the false-reading attacks.
On Sharing Models Instead of Data using Mimic learning for Smart Health Applications
In this paper, we tackle this problem by sharing the models instead of the original sensitive data by using the mimic learning approach.
Mimic Learning to Generate a Shareable Network Intrusion Detection Model
In this paper, we propose the use of mimic learning to enable the transfer of intrusion detection knowledge through a teacher model trained on private data to a student model.
Deep Recurrent Electricity Theft Detection in AMI Networks with Random Tuning of Hyper-parameters
Modern smart grids rely on advanced metering infrastructure (AMI) networks for monitoring and billing pur- poses.
Multiple-Instance, Cascaded Classification for Keyword Spotting in Narrow-Band Audio
We propose using cascaded classifiers for a keyword spotting (KWS) task on narrow-band (NB), 8kHz audio acquired in non-IID environments --- a more challenging task than most state-of-the-art KWS systems face.
