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Found 40 papers, 10 papers with code
CR3DT: Camera-RADAR Fusion for 3D Detection and Tracking
Accurate detection and tracking of surrounding objects is essential to enable self-driving vehicles.
Towards Real-Time Fast Unmanned Aerial Vehicle Detection Using Dynamic Vision Sensors
Unmanned Aerial Vehicles (UAVs) are gaining popularity in civil and military applications.
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
This paper proposes a novel IR-QLoRA for pushing quantized LLMs with LoRA to be highly accurate through information retention.
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Pretrained large language models (LLMs) exhibit exceptional general language processing capabilities but come with significant demands on memory and computational resources.
Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer Interaction: A Comprehensive Survey
To this end, we first sorted the explorations into three domains according to the involved body forms: body-part electric field, whole-body electric field, and body-to-body electric field, and enumerated the state-of-art works in the domains with a detailed survey of the backed sensing tricks and targeted applications.
Angle of Arrival and Centimeter Distance Estimation on a Smart UWB Sensor Node
Accurate and low-power indoor localization is becoming more and more of a necessity to empower novel consumer and industrial applications.
Q-Segment: Segmenting Images In-Sensor for Vessel-Based Medical Diagnosis
We present "Q-Segment", a quantized real-time segmentation algorithm, and conduct a comprehensive evaluation on a low-power edge vision platform with an in-sensors processor, the Sony IMX500.
Retina : Low-Power Eye Tracking with Event Camera and Spiking Hardware
This paper introduces a neuromorphic methodology for eye tracking, harnessing pure event data captured by a Dynamic Vision Sensor (DVS) camera.
Ranked #1 on
Pupil Detection
on INI-30
Evaluation of a Non-Coherent Ultra-Wideband Transceiver for Micropower Sensor Nodes
Spatial and contextual awareness has the potential to revolutionize sensor nodes, enabling spatially augmented data collection and location-based services.
Enhancing Lightweight Neural Networks for Small Object Detection in IoT Applications
Advances in lightweight neural networks have revolutionized computer vision in a broad range of IoT applications, encompassing remote monitoring and process automation.
Quantitative Evaluation of a Multi-Modal Camera Setup for Fusing Event Data with RGB Images
This work quantitatively evaluates a multi-modal camera setup for fusing high-resolution DVS data with RGB image data by static camera alignment.
Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO
To this goal, we designed a smart glasses prototype as a research platform featuring two microcontrollers, including a novel milliwatt-power RISC-V parallel processor with a hardware accelerator for visual AI, and a Bluetooth low-power module for communication.
Ranked #1 on
Object Detection
on PASCAL VOC
Energy-Aware Adaptive Sampling for Self-Sustainability in Resource-Constrained IoT Devices
In the ever-growing Internet of Things (IoT) landscape, smart power management algorithms combined with energy harvesting solutions are crucial to obtain self-sustainability.
Optimizing IoT-Based Asset and Utilization Tracking: Efficient Activity Classification with MiniRocket on Resource-Constrained Devices
Known for its accuracy, scalability, and fast training for time-series classification, in this paper, it is proposed as a TinyML algorithm for inference on resource-constrained IoT devices.
Design and Implementation of an RSSI-Based Bluetooth Low Energy Indoor Localization System
Experimental evaluation with the real-time data processing has been evaluated and presented in a 7. 2 m by 7. 2 m room with furniture and 5 beacon nodes.
Skilog: A Smart Sensor System for Performance Analysis and Biofeedback in Ski Jumping
In particular, a fine-grained control of the center of gravity in the in-run is essential.
Investigation of mmWave Radar Technology For Non-contact Vital Sign Monitoring
At the same distance, the 60 GHz and the 120 GHz radar system shows the least noise level, 0. 0lmm at 0{\deg} angle of incidence, and error in range estimation 0. 64 +- 0. 01 cm and 0. 04 +- 0. 0 cm respectively.
In-Ear-Voice: Towards Milli-Watt Audio Enhancement With Bone-Conduction Microphones for In-Ear Sensing Platforms
Such microphones can record the wearer's speech with much greater isolation, enabling personalized voice activity detection and further audio enhancement applications.
Evaluating Spiking Neural Network On Neuromorphic Platform For Human Activity Recognition
Energy efficiency and low latency are crucial requirements for designing wearable AI-empowered human activity recognition systems, due to the hard constraints of battery operations and closed-loop feedback.
TinyTracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-Sensor for Gaze Estimation
We propose TinyTracker, a highly efficient, fully quantized model for 2D gaze estimation designed to maximize the performance of the edge vision systems considered in this study.
Ranked #2 on
Gaze Estimation
on GazeCapture
Flexible and Fully Quantized Ultra-Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems
With this paper, we demonstrate the suitability and flexibility of TinyissimoYOLO on state-of-the-art detection datasets for real-time ultra-low-power edge inference.
ColibriUAV: An Ultra-Fast, Energy-Efficient Neuromorphic Edge Processing UAV-Platform with Event-Based and Frame-Based Cameras
The interest in dynamic vision sensor (DVS)-powered unmanned aerial vehicles (UAV) is raising, especially due to the microsecond-level reaction time of the bio-inspired event sensor, which increases robustness and reduces latency of the perception tasks compared to a RGB camera.
Fully Automatic Gym Exercises Recording: An IoT Solution
The system we have implemented is a working prototype of a bigger end goal and is supposed to initialize progress toward a smarter, more efficient, and still privacy-respect gym environment in the future.
A Fast and Accurate Optical Flow Camera for Resource-Constrained Edge Applications
The paper characterizes the optical flow sensor in high frame-rate, low-latency settings, with a frame rate of up to 88 fps at the full resolution of 1124 by 1364 pixels and up to 240 fps at a reduced camera resolution of 280 by 336, for both classical camera images and optical flow data.
Parallelizing Optical Flow Estimation on an Ultra-Low Power RISC-V Cluster for Nano-UAV Navigation
On micro and nano UAVs, real-time calculation of the optical flow is run on low power and resource-constrained microcontroller units (MCUs).
TinyissimoYOLO: A Quantized, Low-Memory Footprint, TinyML Object Detection Network for Low Power Microcontrollers
The proposed quantized network architecture with 422k parameters, enables real-time object detection on embedded microcontrollers, and it has been evaluated to exploit CNN accelerators.
Non-invasive urinary bladder volume estimation with artefact-suppressed bio-impedance measurements
Here, a deep learning-based algorithm is presented that processes the local BI of the lower abdomen and suppresses artefacts to measure the bladder volume quantitatively, non-invasively and without the continuous need for additional personnel.
Exploring Automatic Gym Workouts Recognition Locally On Wearable Resource-Constrained Devices
We also introduced an open data set composed of fifty sessions of eleven gym workouts collected from ten subjects that is publicly available.
Self-sustaining Ultra-wideband Positioning System for Event-driven Indoor Localization
The energy consumption for position updates, with an accuracy of $40~cm$ (2D) in realistic non-line-of-sight conditions, is $10. 84~mJ$.
Nonlinear and Machine Learning Analyses on High-Density EEG data of Math Experts and Novices
Our results clarify the different neural signature, analyzed by HFD, of math experts and novices during complex math and suggest machine learning as a promising data-driven approach to understand the brain processes in expertise and mathematical cognition.
Fully On-board Low-Power Localization with Multizone Time-of-Flight Sensors on Nano-UAVs
Experimental evaluation using a nano-UAV open platform demonstrated that the proposed solution is capable of localizing on a 31. 2m$\boldsymbol{^2}$ map with 0. 15m accuracy and an above 95% success rate.
Aerosense: A Self-Sustainable And Long-Range Bluetooth Wireless Sensor Node for Aerodynamic and Aeroacoustic Monitoring on Wind Turbines
This paper presents a low-power, self-sustainable, and modular wireless sensor node for aerodynamic and acoustic measurements on wind turbines and other industrial structures.
MI-BMInet: An Efficient Convolutional Neural Network for Motor Imagery Brain--Machine Interfaces with EEG Channel Selection
A brain--machine interface (BMI) based on motor imagery (MI) enables the control of devices using brain signals while the subject imagines performing a movement.
Sound Event Detection with Binary Neural Networks on Tightly Power-Constrained IoT Devices
This BNN reaches a 77. 9% accuracy, just 7% lower than the full-precision version, with 58 kB (7. 2 times less) for the weights and 262 kB (2. 4 times less) memory in total.
TinyRadarNN: Combining Spatial and Temporal Convolutional Neural Networks for Embedded Gesture Recognition with Short Range Radars
Furthermore, the gesture recognition classifier has been implemented on a Parallel Ultra-Low Power Processor, demonstrating that real-time prediction is feasible with only 21 mW of power consumption for the full TCN sequence prediction network, while a system-level power consumption of less than 100 mW is achieved.
An Accurate EEGNet-based Motor-Imagery Brain-Computer Interface for Low-Power Edge Computing
Our novel method further scales down the standard EEGNet at a negligible accuracy loss of 0. 31% with 7. 6x memory footprint reduction and a small accuracy loss of 2. 51% with 15x reduction.
InfiniWolf: Energy Efficient Smart Bracelet for Edge Computing with Dual Source Energy Harvesting
This work presents InfiniWolf, a novel multi-sensor smartwatch that can achieve self-sustainability exploiting thermal and solar energy harvesting, performing computationally high demanding tasks.
HR-SAR-Net: A Deep Neural Network for Urban Scene Segmentation from High-Resolution SAR Data
Synthetic aperture radar (SAR) data is becoming increasingly available to a wide range of users through commercial service providers with resolutions reaching 0. 5m/px.
FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things
The growing number of low-power smart devices in the Internet of Things is coupled with the concept of "Edge Computing", that is moving some of the intelligence, especially machine learning, towards the edge of the network.
Computationally Efficient Target Classification in Multispectral Image Data with Deep Neural Networks
The required communication links and archiving of the video data are still expensive and this setup excludes preemptive actions to respond to imminent threats.
