1 code implementation • 10 Oct 2023 • Felipe Tellez, Jorge Ortiz
This paper presents a comparative analysis between the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), two vital artificial intelligence algorithms, focusing on optimizing Elliptic Curve Cryptography (ECC) parameters.
no code implementations • 28 Jun 2023 • Yuan Sun, Nandana Pai, Viswa Vijeth Ramesh, Murtadha Aldeer, Jorge Ortiz
The standard approach is based on a CNN model, which our MLP model outperforms. GeXSe offers two types of explanations: sensor-based activation maps and visual domain explanations using short videos.
1 code implementation • 6 Dec 2021 • Tahiya Chowdhury, Murtadha Aldeer, Shantanu Laghate, Jorge Ortiz
We show that by learning a representation specifically with the segmentation objective based on maximum mean discrepancy (MMD), our algorithm can robustly detect time-series events across different applications.
no code implementations • 27 Apr 2021 • Zawar Hussain, Quan Z. Sheng, Wei Emma Zhang, Jorge Ortiz, Seyedamin Pouriyeh
In this paper, we present a comprehensive survey of the latest research works (2015 and after) conducted in various categories of sleep monitoring including sleep stage classification, sleep posture recognition, sleep disorders detection, and vital signs monitoring.
no code implementations • 31 Mar 2021 • Tong Wu, Jorge Ortiz
We introduce a new semi-supervised, time series anomaly detection algorithm that uses deep reinforcement learning (DRL) and active learning to efficiently learn and adapt to anomalies in real-world time series data.
no code implementations • 29 May 2019 • Ayten Ozge Akmandor, Jorge Ortiz, Irene Manotas, Bongjun Ko, Niraj K. Jha
SECRET performs classifications by fusing the semantic information of the labels with the available data: it combines the feature space of the supervised algorithms with the semantic space of the NLP algorithms and predicts labels based on this joint space.
no code implementations • 16 Jan 2018 • Wei-Han Lee, Jorge Ortiz, Bongjun Ko, Ruby Lee
As such, we have seen many recent IoT data sets include annotations with a human expert specifying states, recorded as a set of boundaries and associated labels in a data sequence.
no code implementations • 9 Dec 2015 • Jorge Ortiz, Chien-chin Huang, Supriyo Chakraborty
In this paper, we show that by combining the computing power distributed over a number of phones, judicious optimization choices, and contextual information it is possible to execute the end-to-end pipeline entirely on the phones at the edge of the network, efficiently.
no code implementations • 1 Sep 2015 • Dezhi Hong, Jorge Ortiz, Arka Bhattacharya, Kamin Whitehouse
One important aspect of normalization is to differentiate sensors by the typeof phenomena being observed.