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Found 11 papers, 1 papers with code
MindArm: Mechanized Intelligent Non-Invasive Neuro-Driven Prosthetic Arm System
This demonstrates that our MindArm provides a novel approach for an alternate low-cost mind-controlled prosthetic devices for all patients.
Borrowing Treasures from Neighbors: In-Context Learning for Multimodal Learning with Missing Modalities and Data Scarcity
The proposed data-dependent framework exhibits a higher degree of sample efficiency and is empirically demonstrated to enhance the classification model's performance on both full- and missing-modality data in the low-data regime across various multimodal learning tasks.
MedAide: Leveraging Large Language Models for On-Premise Medical Assistance on Edge Devices
MedAide achieves 77\% accuracy in medical consultations and scores 56 in USMLE benchmark, enabling an energy-efficient healthcare assistance platform that alleviates privacy concerns due to edge-based deployment, thereby empowering the community.
DRL-Based Dynamic Channel Access and SCLAR Maximization for Networks Under Jamming
This paper investigates a deep reinforcement learning (DRL)-based approach for managing channel access in wireless networks.
HgbNet: predicting hemoglobin level/anemia degree from EHR data
EHR-based hemoglobin level/anemia degree prediction is non-invasive and rapid but still faces some challenges due to the fact that EHR data is typically an irregular multivariate time series containing a significant number of missing values and irregular time intervals.
Detection and Localization of Firearm Carriers in Complex Scenes for Improved Safety Measures
By combining these components, our approach achieves exceptional results on a newly proposed dataset.
Localizing Firearm Carriers by Identifying Human-Object Pairs
Visual identification of gunmen in a crowd is a challenging problem, that requires resolving the association of a person with an object (firearm).
Dynamic Matrix Decomposition for Action Recognition
Designing a technique for the automatic analysis of different actions in videos in order to detect the presence of interested activities is of high significance nowadays.
Transfer Learning and Meta Classification Based Deep Churn Prediction System for Telecom Industry
However, the development of a churn prediction system for a telecom industry is a challenging task, mainly due to the large size of the data, high dimensional features, and imbalanced distribution of the data.
Automatic Identification of Closely-related Indian Languages: Resources and Experiments
In this paper, we discuss an attempt to develop an automatic language identification system for 5 closely-related Indo-Aryan languages of India, Awadhi, Bhojpuri, Braj, Hindi and Magahi.
Earthquake magnitude prediction in Hindukush region using machine learning techniques
Earthquake magnitude prediction for Hindukush region has been carried out in this research using the temporal sequence of historic seismic activities in combination with the machine learning classifiers.
