no code implementations • 29 Mar 2024 • Jumman Hossain, Abu-Zaher Faridee, Nirmalya Roy, Jade Freeman, Timothy Gregory, Theron T. Trout
ATAVE is a dynamic probabilistic threat modeling technique that we designed to continuously assess and mitigate potential threats in real-time, enhancing the robot's ability to navigate covertly by adapting to evolving environmental and threat conditions.
no code implementations • 6 Feb 2024 • Jumman Hossain, Abu-Zaher Faridee, Nirmalya Roy, Jade Freeman, Timothy Gregory, Theron T. Trout
Additionally, TopoNav incorporates intrinsic motivation to guide exploration toward relevant regions and frontier nodes in the topological map, addressing the challenges of sparse extrinsic rewards.
no code implementations • 13 Dec 2023 • Vicki Young, Jumman Hossain, Nirmalya Roy
This study presents a comparative analysis between single-objective and multi-objective reinforcement learning methods for training a robot to navigate effectively to an end goal while efficiently avoiding obstacles.
no code implementations • 12 Aug 2023 • Jumman Hossain, Abu-Zaher Faridee, Nirmalya Roy, Anjan Basak, Derrik E. Asher
We evaluate CoverNav using the Unity simulation environment and show that it guarantees dynamically feasible velocities in the terrain when fed with an elevation map generated by another DRL based navigation algorithm.
1 code implementation • 7 Jul 2023 • Zahid Hasan, Abu Zaher Md Faridee, Masud Ahmed, Sanjay Purushotham, Heesung Kwon, Hyungtae Lee, Nirmalya Roy
As an alternative to the traditional pseudo-labeling-based approaches, we leverage the connection between the data sampling and the provided multinoulli (categorical) distribution of novel classes.
no code implementations • 5 May 2023 • Mohammad Saeid Anwar, Emon Dey, Maloy Kumar Devnath, Indrajeet Ghosh, Naima Khan, Jade Freeman, Timothy Gregory, Niranjan Suri, Kasthuri Jayaraja, Sreenivasan Ramasamy Ramamurthy, Nirmalya Roy
Finally, we propose and optimize a novel parameter split-ratio, which indicates the proportion of the data required to be offloaded to another device while considering the networking bandwidth, busy factor, memory (CPU, GPU, RAM), and power constraints of the devices in the testbed.
no code implementations • 3 May 2023 • Maloy Kumar Devnath, Avijoy Chakma, Mohammad Saeid Anwar, Emon Dey, Zahid Hasan, Marc Conn, Biplab Pal, Nirmalya Roy
Image and video data are light and weather-dependent, susceptible to the occlusion effect, and present privacy problems.
1 code implementation • 14 Apr 2023 • Zahid Hasan, Masud Ahmed, Abu Zaher Md Faridee, Sanjay Purushotham, Heesung Kwon, Hyungtae Lee, Nirmalya Roy
During our experiments with UCF101 and multi-view action dataset, NEV-NCD achieves ~ 83% classification accuracy in test instances of labeled data.
no code implementations • 10 Apr 2023 • Lavanya Elluri, Varun Mandalapu, Piyush Vyas, Nirmalya Roy
We start the review with some standard methods cybercriminals use and then focus on the latest machine and deep learning techniques, which detect anomalous behavior and identify potential threats.
no code implementations • 7 Apr 2023 • Avijoy Chakma, Abu Zaher Md Faridee, Indrajeet Ghosh, Nirmalya Roy
Machine learning-based wearable human activity recognition (WHAR) models enable the development of various smart and connected community applications such as sleep pattern monitoring, medication reminders, cognitive health assessment, sports analytics, etc.
no code implementations • 28 Mar 2023 • Varun Mandalapu, Lavanya Elluri, Piyush Vyas, Nirmalya Roy
The study provides access to the datasets used for crime prediction by researchers and analyzes prominent approaches applied in machine learning and deep learning algorithms to predict crime, offering insights into different trends and factors related to criminal activities.
no code implementations • 22 Oct 2022 • Pretom Roy Ovi, Emon Dey, Nirmalya Roy, Aryya Gangopadhyay
We empirically proved the validity of our method with three benchmark datasets and found a minimal accuracy drop in the global model after applying quantization.
1 code implementation • 13 Aug 2022 • Zahid Hasan, Emon Dey, Sreenivasan Ramasamy Ramamurthy, Nirmalya Roy, Archan Misra
In this demo paper, we design and prototype RhythmEdge, a low-cost, deep-learning-based contact-less system for regular HR monitoring applications.
no code implementations • 17 Mar 2020 • Mohammad Arif Ul Alam, Nirmalya Roy, Sarah Holmes, Aryya Gangopadhyay, Elizabeth Galik
Cognitive impairment has become epidemic in older adult population.
no code implementations • 10 Feb 2020 • Neha Singh, Nirmalya Roy, Aryya Gangopadhyay
We investigate the problem of localized flood detection using the social sensing model (Twitter) in order to provide an efficient, reliable and accurate flood text classification model with minimal labeled data.
1 code implementation • 9 Jan 2019 • Nilavra Pathak, James Foulds, Nirmalya Roy, Nilanjan Banerjee, Ryan Robucci
We perform extensive evaluations on two datasets to understand the generative process and show that the Bayesian approach is more interpretable.