… Accordingly, the recent advance‑ ments in technology and Machine Learning (ML) have
led to a more straightforward way to accomplish these tasks. This paper proposes to use Semi‑…

… In recent studies, machine learning-based techniques have been used for hole detection, …
ResNet architectures as the machine learning-based methods for hole quality inspection. …

… who combine the Hough transform algorithm with machine learning algorithms to achieve
very good results in target positioning, size detection, and flaw detection. Cha et al. [22] by …

… The whole dataset with a total number of 480000 samples built from 8 different users was
used, and we divided it into 4 groups of data to perform the machine learning (ie, 120,000 …

… machine learning models that are described below. The next section describes the machine
learning … Hence, combining anomaly detection while continuously updating ML models in …

… Primordial black holes (PBHs) might be formed in the early Universe and could comprise at
… with the hypothesis that all black hole mergers detected so far are of primordial origin. We …

… Autoencoders have already been proven useful in other fields for anomaly detection, so
we see great potential in this application in semiconductor process control [8, 9, 10]. …

… In this paper, machine learning is applied to ADU … machine learning to ADU data is
beneficial as drilling in the aerospace industry shows high repeatability and many produced holes…

… the overview of machine learning and classification techniques along with the related work
that utilizes a mobile sensor for detecting pot-holes. … Machine learning and classification …

… In Section 3 we give an overview of the methodological approach followed during the
high-level design of the solution; in Section 4 we provide details on the Machine Learning core of …