Artificial intelligence in the IoT era: A review of edge AI hardware and software
T Sipola, J Alatalo, T Kokkonen… - 2022 31st Conference …, 2022 - ieeexplore.ieee.org
The modern trend of moving artificial intelligence computation near to the origin of data
sources has increased the demand for new hardware and software suitable for such …
sources has increased the demand for new hardware and software suitable for such …
Federated learning enables big data for rare cancer boundary detection
Although machine learning (ML) has shown promise across disciplines, out-of-sample
generalizability is concerning. This is currently addressed by sharing multi-site data, but …
generalizability is concerning. This is currently addressed by sharing multi-site data, but …
Spqr: A sparse-quantized representation for near-lossless llm weight compression
Recent advances in large language model (LLM) pretraining have led to high-quality LLMs
with impressive abilities. By compressing such LLMs via quantization to 3-4 bits per …
with impressive abilities. By compressing such LLMs via quantization to 3-4 bits per …
Anomalib: A deep learning library for anomaly detection
S Akcay, D Ameln, A Vaidya… - … on Image Processing …, 2022 - ieeexplore.ieee.org
This paper introduces anomalib 1, a novel library for unsupervised anomaly detection and
localization. With reproducibility and modularity in mind, this open-source library provides …
localization. With reproducibility and modularity in mind, this open-source library provides …
Robotic guide dog: Leading a human with leash-guided hybrid physical interaction
An autonomous robot that is able to physically guide humans through narrow and cluttered
spaces could be a big boon to the visually-impaired. Most prior robotic guiding systems are …
spaces could be a big boon to the visually-impaired. Most prior robotic guiding systems are …
[PDF][PDF] A survey of efficient deep learning models for moving object segmentation
Moving object segmentation (MOS) is the process of identifying dynamic objects from video
frames, such as moving vehicles or pedestrians, while discarding the background. It plays …
frames, such as moving vehicles or pedestrians, while discarding the background. It plays …
Autonomous, onboard vision-based trash and litter detection in low altitude aerial images collected by an unmanned aerial vehicle
Public littering and discarded trash are, despite the effort being put to limit it, still a serious
ecological, aesthetic, and social problem. The problematic waste is usually localised and …
ecological, aesthetic, and social problem. The problematic waste is usually localised and …
Using computer vision to enhance safety of workforce in manufacturing in a post covid world
P Khandelwal, A Khandelwal, S Agarwal… - arXiv preprint arXiv …, 2020 - arxiv.org
The COVID-19 pandemic forced governments across the world to impose lockdowns to
prevent virus transmissions. This resulted in the shutdown of all economic activity and …
prevent virus transmissions. This resulted in the shutdown of all economic activity and …
Toward accurate post-training quantization for image super resolution
Abstract Model quantization is a crucial step for deploying super resolution (SR) networks on
mobile devices. However, existing works focus on quantization-aware training, which …
mobile devices. However, existing works focus on quantization-aware training, which …
A smart system for personal protective equipment detection in industrial environments based on deep learning at the edge
G Gallo, F Di Rienzo, F Garzelli, P Ducange… - IEEE …, 2022 - ieeexplore.ieee.org
Real-time object detection is currently used to automate various tasks in industrial
environments. One of the most important tasks is to improve the safety of workers by …
environments. One of the most important tasks is to improve the safety of workers by …