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 In today's applications, a significant increase in the use of deep learning algorithms is noticeable. The convolution neural network (CNN) of deep learning has been used frequently recently, especially for the successful discrimination of people and vehicles …

Robust object detection and classification in dynamic industrial scenarios is still a challenge, in particular if the system has to work in real-time on mid-ranged hardware. Classical vision-based methods have difficulties to cope with low/weak illumination, r…

Handwritten Signature Recognition (HSR) is a vital task in document authentication and verification systems. This paper proposes a novel approach for offline HSR leveraging pre-trained Convolutional Neural Network (CNN) models. CNNs have demonstrated remarkabl…

The incidence of skin cancer is increasing. Early detection of cases of skin cancer is vital for treatment. Recently, computerized methods have been widely used in cancer diagnosis. These methods have important advantages such as no human error, short diagnosi…

In this study, it is aimed to develop a deep learning application which detects types of garbage into trash in order to provide recyclability with vision system. Training and testing will be performed with image data consisting of several classes on differen…