2 citations · 5 across the 13 of their papers we have counts for
13 papers
Efficient Neural Network Model Selection for Few-Class Application Datasets
Bryan Bo Cao, Abhinav Sharma, Lawrence O'Gorman +2
While much effort has focused on developing and benchmarking high-performance neural networks, less attention has been given to how dataset properties, known to practitioners, can…
FeudalNav: A Simple Framework for Visual Navigation
Faith Johnson, Bryan Bo Cao, Shubham Jain +2
Visual navigation for robotics is inspired by the human ability to navigate environments using visual cues and memory, eliminating the need for detailed maps. In unseen, unmapped,…
YOPO-Nav: Visual Navigation using 3DGS Graphs from One-Pass Videos
Ryan Meegan, Adam D'Souza, Bryan Bo Cao +2
Visual navigation has emerged as a practical alternative to traditional robotic navigation pipelines that rely on detailed mapping and path planning. However, constructing and main…
StatsMerging: Statistics-Guided Model Merging via Task-Specific Teacher Distillation
Ranjith Merugu, Bryan Bo Cao, Shubham Jain
Model merging has emerged as a promising solution to accommodate multiple large models within constrained memory budgets. We present StatsMerging, a novel lightweight learning-base…
Memory Proxy Maps for Visual Navigation
Faith Johnson, Bryan Bo Cao, Ashwin Ashok +2
Visual navigation takes inspiration from humans, who navigate in previously unseen environments using vision without detailed environment maps. Inspired by this, we introduce a nov…
Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement
Bryan Bo Cao, Lawrence O'Gorman, Michael Coss +1
We propose Few-Class Arena (FCA), as a unified benchmark with focus on testing efficient image classification models for few classes. A wide variety of benchmark datasets with many…
Representation Similarity: A Better Guidance of DNN Layer Sharing for Edge Computing without Training
Bryan Bo Cao, Abhinav Sharma, Manavjeet Singh +3
Edge computing has emerged as an alternative to reduce transmission and processing delay and preserve privacy of the video streams. However, the ever-increasing complexity of Deep…
A Lightweight Measure of Classification Difficulty from Application Dataset Characteristics
Bryan Bo Cao, Abhinav Sharma, Lawrence O'Gorman +2
Although accuracy and computation benchmarks are widely available to help choose among neural network models, these are usually trained on datasets with many classes, and do not gi…
A Landmark-Aware Visual Navigation Dataset
Faith Johnson, Bryan Bo Cao, Kristin Dana +2
Map representations learned by expert demonstrations have shown promising research value. However, the field of visual navigation still faces challenges due to the lack of real-wor…
Feudal Networks for Visual Navigation
Faith Johnson, Bryan Bo Cao, Ashwin Ashok +2
Visual navigation follows the intuition that humans can navigate without detailed maps. A common approach is interactive exploration while building a topological graph with images…
ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements
Bryan Bo Cao, Abrar Alali, Hansi Liu +5
Tracking subjects in videos is one of the most widely used functions in camera-based IoT applications such as security surveillance, smart city traffic safety enhancement, vehicle…
Data-Side Efficiencies for Lightweight Convolutional Neural Networks
Bryan Bo Cao, Lawrence O'Gorman, Michael Coss +1
We examine how the choice of data-side attributes for two important visual tasks of image classification and object detection can aid in the choice or design of lightweight convolu…
ViFiCon: Vision and Wireless Association Via Self-Supervised Contrastive Learning
Nicholas Meegan, Hansi Liu, Bryan Bo Cao +5
We introduce ViFiCon, a self-supervised contrastive scheme which learns a cross-modal association between vision and wireless modalities. Specifically, the system uses pedestrian d…