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Found 25 papers, 3 papers with code
H3DFact: Heterogeneous 3D Integrated CIM for Factorization with Holographic Perceptual Representations
Disentangling attributes of various sensory signals is central to human-like perception and reasoning and a critical task for higher-order cognitive and neuro-symbolic AI systems.
Towards Cognitive AI Systems: a Survey and Prospective on Neuro-Symbolic AI
The remarkable advancements in artificial intelligence (AI), primarily driven by deep neural networks, have significantly impacted various aspects of our lives.
Real-Time Fully Unsupervised Domain Adaptation for Lane Detection in Autonomous Driving
While deep neural networks are being utilized heavily for autonomous driving, they need to be adapted to new unseen environmental conditions for which they were not trained.
Non-Uniform Interpolation in Integrated Gradients for Low-Latency Explainable-AI
Integrated Gradients (IG) is a popular XAI algorithm that attributes relevance scores to input features commensurate with their contribution to the model's output.
Gradient Backpropagation based Feature Attribution to Enable Explainable-AI on the Edge
In this work, we first analyze the dataflow of gradient backpropagation based feature attribution algorithms to determine the resource overhead required over inference.
Fusing Frame and Event Vision for High-speed Optical Flow for Edge Application
However, the algorithms for processing the data either borrow frame like setup limiting the speed or suffer from lower accuracy.
FRL-FI: Transient Fault Analysis for Federated Reinforcement Learning-Based Navigation Systems
Swarm intelligence is being increasingly deployed in autonomous systems, such as drones and unmanned vehicles.
RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning
To address this challenge, we propose a reconfigurable architecture with preemptive exits for efficient deep RL (RAPID-RL).
iELAS: An ELAS-Based Energy-Efficient Accelerator for Real-Time Stereo Matching on FPGA Platform
Stereo matching is a critical task for robot navigation and autonomous vehicles, providing the depth estimation of surroundings.
An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on FPGA Platform
In our past few years' of commercial deployment experiences, we identify localization as a critical task in autonomous machine applications, and a great acceleration target.
Multi-Task Federated Reinforcement Learning with Adversaries
Experimentation on different small to mid-size reinforcement learning problems show that the proposed attack method outperforms other general attack methods and the proposed modification to federated reinforcement learning algorithm was able to achieve near-optimal policies in the presence of adversarial agents.
A Survey of FPGA-Based Robotic Computing
On the other hand, FPGA-based robotic accelerators are becoming increasingly competitive alternatives, especially in latency-critical and power-limited scenarios.
Masked Face Recognition for Secure Authentication
The use of these face masks has raised a serious question on the accuracy of the facial recognition system used for tracking school/office attendance and to unlock phones.
A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning
We develop a mathematical framework for solving multi-task reinforcement learning (MTRL) problems based on a type of policy gradient method.
Counting Cards: Exploiting Variance and Data Distributions for Robust Compute In-Memory
Compute in-memory (CIM) is a promising technique that minimizes data transport, the primary performance bottleneck and energy cost of most data intensive applications.
Bio-inspired Gait Imitation of Hexapod Robot Using Event-Based Vision Sensor and Spiking Neural Network
When humans watch their peers, visual data is processed through a visual cortex in the brain.
Learning to Walk: Spike Based Reinforcement Learning for Hexapod Robot Central Pattern Generation
However, training a legged robot to walk by learning the synchronization patterns of central pattern generators (CPG) in an SNN framework has not been shown.
Hardware-aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices
Deep neural networks (DNNs) have been emerged as the state-of-the-art algorithms in broad range of applications.
Autonomous Navigation via Deep Reinforcement Learning for Resource Constraint Edge Nodes using Transfer Learning
Smart and agile drones are fast becoming ubiquitous at the edge of the cloud.
Design space exploration of Ferroelectric FET based Processing-in-Memory DNN Accelerator
In this letter, we quantify the impact of device limitations on the classification accuracy of an artificial neural network, where the synaptic weights are implemented in a Ferroelectric FET (FeFET) based in-memory processing architecture.
Appearance-based Gesture recognition in the compressed domain
We propose a novel appearance-based gesture recognition algorithm using compressed domain signal processing techniques.
Direct Feedback Alignment with Sparse Connections for Local Learning
Using a sparse feedback matrix, we show that a neuron needs only a fraction of the information previously used by the feedback alignment algorithms.
NAVREN-RL: Learning to fly in real environment via end-to-end deep reinforcement learning using monocular images
We present NAVREN-RL, an approach to NAVigate an unmanned aerial vehicle in an indoor Real ENvironment via end-to-end reinforcement learning RL.
Stochastic IMT (insulator-metal-transition) neurons: An interplay of thermal and threshold noise at bifurcation
This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance.
A Light-powered, Always-On, Smart Camera with Compressed Domain Gesture Detection
In this paper we propose an energy-efficient camera-based gesture recognition system powered by light energy for "always on" applications.
