Enhancing Digital Image Forgery Detection Using Transfer Learning

Nowadays, digital images are a main source of shared information in social media. Meanwhile, malicious software can forge such images for fake information. So, it’s crucial to identify these forgeries. This problem was tackled in the literature by various digital image forgery detection techniques. But most of these techniques are tied to detec...

ENRICHING THE TRANSFER LEARNING WITH PRE-TRAINED LEXICON EMBEDDINGFOR LOW-RESOURCE NEURAL MACHINE TRANSLATION

Most State-Of-The-Art (SOTA) Neural Machine Translation (NMT) systems today achieve outstanding results based only on large parallel corpora. The large-scale parallel corpora for high-resource languages is easily obtainable. However, the translation quality of NMT for morphologically rich languages is still unsatisfactory, mainly because of the dat...

AN ONLINE TRANSFER LEARNING FRAMEWORK WITH EXTREME LEARNING MACHINFOR AUTOMATED CREDIT SCORINGE

Automated Credit Scoring (ACS) is the process of predicting user credit based on historical data. It involves analyzing and predicting the association between the data and particular credit values based on similar data. Recently, ACS has been handled as a machine learning problem, and numerous models were developed to address it. In this paper, we ...

A HYBRID CLOUD AND EDGE CONTROL STRATEGY FOR DEMAND RESPONSES USING DEEP REINFORCEMENT LEARNING AND TRANSFER LEARNING

A HYBRID CLOUD AND EDGE CONTROL STRATEGY FOR DEMAND RESPONSES USING DEEP REINFORCEMENT LEARNING AND TRANSFER LEARNING...