[HTML][HTML] Early weed identification based on deep learning: A review
Y Zhang, M Wang, D Zhao, C Liu, Z Liu - Smart Agricultural Technology, 2023 - Elsevier
Weeds were one of the most destructive constraints on crop production and posed a
significant threat to agricultural productivity. The increasing development of smart agriculture …
significant threat to agricultural productivity. The increasing development of smart agriculture …
Efficient automation of neural network design: A survey on differentiable neural architecture search
In the past few years, Differentiable Neural Architecture Search (DNAS) rapidly imposed
itself as the trending approach to automate the discovery of deep neural network …
itself as the trending approach to automate the discovery of deep neural network …
Manas: multi-agent neural architecture search
Abstract The Neural Architecture Search (NAS) problem is typically formulated as a graph
search problem where the goal is to learn the optimal operations over edges in order to …
search problem where the goal is to learn the optimal operations over edges in order to …
[HTML][HTML] Are neural architecture search benchmarks well designed? A deeper look into operation importance
Abstract Neural Architecture Search (NAS) benchmarks significantly improved the capability
of developing and comparing NAS methods while at the same time drastically reduced the …
of developing and comparing NAS methods while at the same time drastically reduced the …
Lightweight multi-objective evolutionary neural architecture search with low-cost proxy metrics
Abstract Multi-Objective Evolutionary Neural Architecture Search (MOENAS) methods
employ evolutionary algorithms to approximate a set of architectures representing optimal …
employ evolutionary algorithms to approximate a set of architectures representing optimal …
Toward Less Constrained Macro-Neural Architecture Search
V Lopes, LA Alexandre - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
Networks found with neural architecture search (NAS) achieve the state-of-the-art
performance in a variety of tasks, out-performing human-designed networks. However, most …
performance in a variety of tasks, out-performing human-designed networks. However, most …
Understanding and accelerating neural architecture search with training-free and theory-grounded metrics
This work targets designing a principled and unified training-free framework for Neural
Architecture Search (NAS), with high performance, low cost, and in-depth interpretation …
Architecture Search (NAS), with high performance, low cost, and in-depth interpretation …
MANAS: Multi-agent neural architecture search
The Neural Architecture Search (NAS) problem is typically formulated as a graph search
problem where the goal is to learn the optimal operations over edges in order to maximise a …
problem where the goal is to learn the optimal operations over edges in order to maximise a …
Deep architecture connectivity matters for its convergence: A fine-grained analysis
Advanced deep neural networks (DNNs), designed by either human or AutoML algorithms,
are growing increasingly complex. Diverse operations are connected by complicated …
are growing increasingly complex. Diverse operations are connected by complicated …
Latency-aware Neural Architecture Performance Predictor with Query-to-Tier Technique
Neural Architecture Search (NAS) is a powerful tool for automating effective image and
video processing DNN designing. The ranking of the accuracy has been advocated to …
video processing DNN designing. The ranking of the accuracy has been advocated to …