Students should be able to: a) develop basic computational thinking b) explain and use data types c) appreciate the notion of algorithms d) develop a basic understanding of computer systems- ...

Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically. Classic models like regression, decision trees, and KNN remain important in modern AI ...

To address the issues of feature mismatching and map overlap drift in simultaneous localization and mapping (SLAM) within degraded environments characterized by sparse geometric features or severe ...

In this paper, we analyze two popular network compression techniques, i.e. filter pruning and low-rank decomposition, in a unified sense. By simply changing the way the sparsity regularization is ...

Abstract: A method of enhancing signal-to-noise ratio (SNR) in Brillouin optical time domain reflectometer (BOTDR) is proposed using sparse reconstruction of the Brillouin gain spectrum (BGS) matrix.

Abstract: Nowadays a computer programming become the fundamental knowledge for people studying or working in a computer field, e.g. computer engineering, computer science, information technology, etc.

Forbes contributors publish independent expert analyses and insights. CEOs can use ChatGPT prompts to "clone" their decision-making, automating repetitive tasks and scaling their impact. This involves ...

ESET took part in a coordinated global operation to disrupt Lumma Stealer. ESET provided technical analysis and statistical information, and extracted essential data from tens of thousands of malware ...

Choosing the right algorithm for machine learning can make a huge difference in making your model very effective. Of many algorithms, two popular choices have been Decision Trees and Random Forests ...

The growing demand for solar energy conversion underscores the need for precise parameter extraction methods in photovoltaic (PV) plants. This study focuses on enhancing accuracy in PV system ...

In this study, we were aimed to identify important variables via machine learning algorithms and predict postoperative delirium (POD) occurrence in older patients. This study was to make the secondary ...