Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Woubie, Abraham"'
Autor:
Solomon, Enoch, Woubie, Abraham
The state-of-the-art face recognition systems are typically trained on a single computer, utilizing extensive image datasets collected from various number of users. However, these datasets often contain sensitive personal information that users may h
Externí odkaz:
http://arxiv.org/abs/2403.05344
Although deep learning are commonly employed for image recognition, usually huge amount of labeled training data is required, which may not always be readily available. This leads to a noticeable performance disparity when compared to state-of-the-ar
Externí odkaz:
http://arxiv.org/abs/2312.14395
The primary objective of this work is to present an alternative approach aimed at reducing the dependency on labeled data. Our proposed method involves utilizing autoencoder pre-training within a face image recognition task with two step processes. I
Externí odkaz:
http://arxiv.org/abs/2312.14301
Achieving state-of-the-art results in face verification systems typically hinges on the availability of labeled face training data, a resource that often proves challenging to acquire in substantial quantities. In this research endeavor, we proposed
Externí odkaz:
http://arxiv.org/abs/2312.14001
In various verification systems, Restricted Boltzmann Machines (RBMs) have demonstrated their efficacy in both front-end and back-end processes. In this work, we propose the use of RBMs to the image clustering tasks. RBMs are trained to convert image
Externí odkaz:
http://arxiv.org/abs/2312.13845
The COVID-19 outbreak disrupted different organizations, employees and students, who turned to teleconference applications to collaborate and socialize even during the quarantine. Thus, the demand of teleconferencing applications surged with mobile a
Externí odkaz:
http://arxiv.org/abs/2010.09488
In recent years, transformer models have achieved great success in natural language processing (NLP) tasks. Most of the current state-of-the-art NLP results are achieved by using monolingual transformer models, where the model is pre-trained using a
Externí odkaz:
http://arxiv.org/abs/2006.07698
Mapping states to actions in deep reinforcement learning is mainly based on visual information. The commonly used approach for dealing with visual information is to extract pixels from images and use them as state representation for reinforcement lea
Externí odkaz:
http://arxiv.org/abs/1905.04192
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