This project uses wavelet-based feature extraction, and Naive Bayes' Machine Learning model to screen arrhythmia signals from normal ECG (⭐ 5)
In this paper we present a bilevel optimization scheme for the solution of a general image deblurring problem, in which a parametric variational-like approach is encapsulated within a machine learning scheme to provide a high quality reconstructed im...
Art curatorial practice is characterized by the presentation of an art collection in a knowledgeable way. Machine processes are characterized by their capacity to manage and analyze large amounts of data. This paper envisages AI curation and audience...
To ensure the security of the general mass, crime prevention is one of the most higher priorities for any government. An accurate crime prediction model can help the government, law enforcement to prevent violence, detect the criminals in advance, al...
Machine learning is advancing rapidly, with applications bringing notable benefits, such as improvements in translation and code generation. Models like ChatGPT, powered by Large Language Models (LLMs), are increasingly integrated into daily life. Ho...
Designed to enlarge a pre-drilled hole and easily produce a complex form. Inch, Metric, British Sizes. Bearing Locknut Sizes. Specials in Hex or Round. Inch and Metric. Stub, Regular, Taper Length, …
The softmax (also called softargmax) function is widely used in machine learning models to normalize real-valued scores into a probability distribution. To avoid floating-point overflow, the softmax function is conventionally implemented in three pas...
Recent years have seen a surge in the popularity of commercial AI products based on generative, multi-purpose AI systems promising a unified approach to building machine learning (ML) models into technology. However, this ambition of ``generality'' c...
Marc Benioff Cherie Blair Bernhard Schölkopf Yann LeCun Michele Woods Sasha Luccioni Kate Kallot Anne Bouverot The ITU-T Focus Group on Machine Learning
Jan 8, 2008 · Does anyone here do any modifications to their machine to harvest edible beans? If so, what do you do to the combine?
Equipment Maintenance Products Industrial equipment requires consistent maintenance to ensure safety, compliance, and machine longevity. By partnering with an experienced chemical provider, …
Teamworks Intelligence, formerly Zelus Analytics, uses advanced machine learning to deliver sport-specific predictive models and metrics that inform everything from athlete evaluation and roster …
Consider a set of jobs with independent random service times to be scheduled on a single machine. The jobs can be surgeries in an operating room, patients' appointments in outpatient clinics, etc. The challenge is to determine the optimal sequence an...
Nonconvex-nonconcave minimax problems have found numerous applications in various fields including machine learning. However, questions remain about what is a good surrogate for local minimax optimum and how to characterize the minimax optimality. Re...
This paper aims at developing an automatic algorithm for moth recognition from trap images in real-world conditions. This method uses our previous work for detection [1] and introduces an adapted classification step. More precisely, SVM classifier is...
We seek to (i) characterize the learning architectures exploited in biological neural networks for training on very few samples, and (ii) port these algorithmic structures to a machine learning context. The Moth Olfactory Network is among the simples...
Machine learning to classify Malicious (Spam)/Benign URL's (⭐ 134)
We present a formal proof in Lean of probably approximately correct (PAC) learnability of the concept class of decision stumps. This classic result in machine learning theory derives a bound on error probabilities for a simple type of classifier. Tho...
Integrity is critical for maintaining system security, as it ensures that only genuine software is loaded onto a machine. Although confidential virtual machines (CVMs) function within isolated environments separate from the host, it is important to r...
Federated Learning (FL) is a distributed machine learning approach that has emerged as an effective way to address recent privacy concerns. However, FL introduces the need for additional security measures as FL alone is still subject to vulnerabiliti...