VLDB 2026 Research / reviewers in the wild / expert
Atul Bansal
dblp:31/5915
· DBLP profile ↗
13ranked-venue papers
2as first author
10since 2021 · last 2024
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 8 · 6 since 2021Computer networks · 4 · 2 first-author · 3 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Towards Ubiquitous IoT through Long Range Wireless Energy HarvestingabstractExtending the range of RF energy harvesting can revolutionize battery-free/low-power sensing and networking. This paper explores the design space for RF infrastructure to charge battery-free devices (e.g. RFID) or devices with coin-cell batteries (e.g. water and security sensors) over much longer range than the state-of-the-art. Rather than rely completely on ambient RF (e.g. TV towers) or dedicated infrastructure (e.g. RFID readers), we explore a middle path - combine RF energy from (nearly) all available major wireless frequency bands and then supplement this with low-cost specially designed RF charging infrastructure to fill in any gaps. Mohamed Ibrahim Ahmed 0001, Atul Bansal, Kuang Yuan, Junbo Zhang 0001, Swarun Kumar |
MobiHoc | 2 |
| 2023 | Battery-free Wideband Spectrum Mapping using Commodity RFID TagsabstractThis paper introduces RFIMap, a system that aims to inexpensively characterize the spatial and temporal distribution of RF spectrum occupancy of any indoor space at fine granularity (tens of centimeters). RFIMap builds rich wide-band indoor spectrum occupancy maps using low-cost and battery-free commodity RFID tags. RFIMap's spectrum maps have wide-ranging applications such as monitoring ambient interference in smart manufacturing, and smart hospitals. RFIMap relies on the observation that commodity RFID tags naturally reflect ambient transmission at other frequency bands, without any modification. RFIMap uses these reflections to estimate the ambient signal power originally received at these tags. RFIMap further performs a careful modeling of indoor multipath to build a dense spectrum map with fine spatial granularity. Our experiments demonstrate spatial spectrum measurement with 2.15 dB of median error at 2.4 GHz, 4.45 dB of median error at 470-700 MHz TV whitespace band, 2.1 dB of median error at 1.8-1.9 GHz in diverse industrial and university settings. Mohamed Ibrahim Ahmed 0001, Atul Bansal, Kuang Yuan, Swarun Kumar, Peter Steenkiste |
MobiCom | 2 |
| 2023 | Machine learning & computer vision-based optimum black tea fermentation detection
Anuja Bhargava, Atul Bansal, Vishal Goyal, Aasheesh Shukla |
Multim. Tools Appl. | 2 |
| 2022 | Machine learning-based automatic detection of novel coronavirus (COVID-19) disease
Anuja Bhargava, Atul Bansal, Vishal Goyal |
Multim. Tools Appl. | 2 |
| 2022 | A novel diabetic retinopathy grading using modified deep neural network with segmentation of blood vessels and retinal abnormalities
Paresh Chandra Sau, Atul Bansal |
Multim. Tools Appl. | 2 |
| 2022 | An alignment-free non-invertible transformation-based method for generating the cancellable fingerprint template
Diwakar Agarwal, Atul Bansal |
Pattern Anal. Appl. | 2 |
| 2021 | OwLL: Accurate LoRa Localization using the TV WhitespacesabstractLoRa is a popular Low-Power Wide-Area Networking (LP-WAN) technology that allows devices powered by a ten year AA battery to connect to radio infrastructure miles away. One of the most promising features of LoRa is the ability to track the location of radios from a distance, enabling applications ranging from inventory tracking, smart infrastructure monitoring and structural health sensing. Yet, state-of-the-art LoRa localization systems experience errors of several tens or even hundreds of meters in location tracking, owing to the narrow bandwidth and limited battery life of LoRa devices. Atul Bansal, Akshay Gadre, Vaibhav Singh 0001, Anthony Rowe 0001, Bob Iannucci, Swarun Kumar |
IPSN | 1 |
| 2021 | A utility of pores as level 3 features in latent fingerprint identification
Diwakar Agarwal, Atul Bansal |
Multim. Tools Appl. | 2 |
| 2021 | Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review
Anuja Bhargava, Atul Bansal |
Multim. Tools Appl. | 2 |
| 2021 | A comprehensive review on soil classification using deep learning and computer vision techniques
Pallavi Srivastava, Aasheesh Shukla, Atul Bansal |
Multim. Tools Appl. | 3 |
| 2020 | Does ambient RF energy suffice to power battery-free IoT?abstractRecent years have witnessed novel designs of battery-free IoT tags using RF backscatter. Traditionally, they require a dedicated transmitter to excite the tag. However, such a deployment is infeasible at large scale. To counter this problem, researchers have proposed using ambient RF energy to power up the battery-free tag. In this poster, we evaluate if this ambient RF energy is sufficient to meet the power requirements of a battery-free tag in today's urban and rural areas. We also compare available ambient RF energy across different frequencies. Finally, we discuss open challenges in realising ambient backscatter systems in real-world. Atul Bansal, Swarun Kumar, Bob Iannucci |
MobiSys | 1 |
| 2020 | Quality evaluation of Mono & bi-Colored Apples with computer vision and multispectral imaging
Anuja Bhargava, Atul Bansal |
Multim. Tools Appl. | 2 |
| 2020 | Machine learning based quality evaluation of mono-colored apples
Anuja Bhargava, Atul Bansal |
Multim. Tools Appl. | 2 |