21 citations · 37 across the 7 of their papers we have counts for
8 papers
EmoPhone: A Multi-Wave Dataset for In-the-Wild Mobile and Wearable Affect Sensing
Panyu Zhang, Minseo Park, Soowon Kang +7
We introduce a three-wave, in-the-wild multimodal dataset for affect sensing that integrates smartphone sensing, wearable sensing, and dense experience-sampling-method (ESM) labels…
LITE: A Paradigm Shift in Multi-Object Tracking with Efficient ReID Feature Integration
Jumabek Alikhanov, Dilshod Obidov, Hakil Kim
The Lightweight Integrated Tracking-Feature Extraction (LITE) paradigm is introduced as a novel multi-object tracking (MOT) approach. It enhances ReID-based trackers by eliminating…
Edge Device Deployment of Multi-Tasking Network for Self-Driving Operations
Shokhrukh Miraliev, Shakhboz Abdigapporov, Jumabek Alikhanov +2
A safe and robust autonomous driving system relies on accurate perception of the environment for application-oriented scenarios. This paper proposes deployment of the three most cr…
Toward Data-Driven Digital Therapeutics Analytics: Literature Review and Research Directions
Uichin Lee, Gyuwon Jung, Eun-Yeol Ma +5
With the advent of Digital Therapeutics (DTx), the development of software as a medical device (SaMD) for mobile and wearable devices has gained significant attention in recent yea…
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data
Azizjon Meliboev, Jumabek Alikhanov, Wooseong Kim
Intrusion detection system (IDS) plays an essential role in computer networks protecting computing resources and data from outside attacks. Recent IDS faces challenges improving fl…
W-Net: A CNN-based Architecture for White Blood Cells Image Classification
Changhun Jung, Mohammed Abuhamad, Jumabek Alikhanov +3
Computer-aided methods for analyzing white blood cells (WBC) have become widely popular due to the complexity of the manual process. Recent works have shown highly accurate segment…
Rule Based Metadata Extraction Framework from Academic Articles
Jahongir Azimjonov, Jumabek Alikhanov
Metadata of scientific articles such as title, abstract, keywords or index terms, body text, conclusion, reference and others play a decisive role in collecting, managing and stori…
Transfer Learning Based on AdaBoost for Feature Selection from Multiple ConvNet Layer Features
Jumabek Alikhanov, Myeong Hyeon Ga, Seunghyun Ko +1
Convolutional Networks (ConvNets) are powerful models that learn hierarchies of visual features, which could also be used to obtain image representations for transfer learning. The…