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20202022
most citedCollaborative Intelligence: Challenges and Opportunities

18 citations · 28 across the 11 of their papers we have counts for

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eess.IV2022

Privacy-Preserving Feature Coding for Machines

Bardia Azizian, Ivan V. Bajić

Automated machine vision pipelines do not need the exact visual content to perform their tasks. Therefore, there is a potential to remove private information from the data without…

eess.IV20222 cited

Practical Noise Simulation for RGB Images

Saeed Ranjbar Alvar, Ivan V. Bajić

This document describes a noise generator that simulates realistic noise found in smartphone cameras. The generator simulates Poissonian-Gaussian noise whose parameters have been e…

eess.IV2021

CALTeC: Content-Adaptive Linear Tensor Completion for Collaborative Intelligence

Ashiv Dhondea, Robert A. Cohen, Ivan V. Bajić

In collaborative intelligence, an artificial intelligence (AI) model is typically split between an edge device and the cloud. Feature tensors produced by the edge sub-model are sen…

eess.IV2021

Error Resilient Collaborative Intelligence via Low-Rank Tensor Completion

Lior Bragilevsky, Ivan V. Bajić

In the race to bring Artificial Intelligence (AI) to the edge, collaborative intelligence has emerged as a promising way to lighten the computation load on edge devices that run ap…

eess.IV2021

Swimmer Stroke Rate Estimation From Overhead Race Video

Timothy Woinoski, Ivan V. Bajić

In this work, we propose a swimming analytics system for automatically determining swimmer stroke rates from overhead race video (ORV). General ORV is defined as any footage of swi…

eess.IV202118 cited

Collaborative Intelligence: Challenges and Opportunities

Ivan V. Bajić, Weisi Lin, Yonghong Tian

This paper presents an overview of the emerging area of collaborative intelligence (CI). Our goal is to raise awareness in the signal processing community of the challenges and opp…