625 citations · 689 across the 8 of their papers we have counts for
8 papers
Adaptive Label Smoothing for Out-of-Distribution Detection
Mingle Xu, Jaehwan Lee, Sook Yoon +1
Out-of-distribution (OOD) detection, which aims to distinguish unknown classes from known classes, has received increasing attention recently. A main challenge within is the unavai…
Plant Disease Recognition Datasets in the Age of Deep Learning: Challenges and Opportunities
Mingle Xu, Ji Eun Park, Jaehwan Lee +2
Plant disease recognition has witnessed a significant improvement with deep learning in recent years. Although plant disease datasets are essential and many relevant datasets are p…
Large Language Models and Foundation Models in Smart Agriculture: Basics, Opportunities, and Challenges
Jiajia Li, Mingle Xu, Lirong Xiang +4
The past decade has witnessed the rapid development and adoption of ML & DL methodologies in agricultural systems, showcased by great successes in agricultural applications. Howeve…
Towards Understanding Gradient Approximation in Equality Constrained Deep Declarative Networks
Stephen Gould, Ming Xu, Zhiwei Xu +1
We explore conditions for when the gradient of a deep declarative node can be approximated by ignoring constraint terms and still result in a descent direction for the global loss…
Adaptive Frequency Green Light Optimal Speed Advisory based on Hybrid Actor-Critic Reinforcement Learning
Ming Xu, Dongyu Zuo
Green Light Optimal Speed Advisory (GLOSA) system suggests speeds to vehicles to assist them in passing through intersections during green intervals, thus reducing traffic congesti…
Embrace Limited and Imperfect Training Datasets: Opportunities and Challenges in Plant Disease Recognition Using Deep Learning
Mingle Xu, Hyongsuk Kim, Jucheng Yang +5
Recent advancements in deep learning have brought significant improvements to plant disease recognition. However, achieving satisfactory performance often requires high-quality tra…
Variation-Aware Semantic Image Synthesis
Mingle Xu, Jaehwan Lee, Sook Yoon +2
Semantic image synthesis (SIS) aims to produce photorealistic images aligning to given conditional semantic layout and has witnessed a significant improvement in recent years. Alth…
A Comprehensive Survey of Image Augmentation Techniques for Deep Learning
Mingle Xu, Sook Yoon, Alvaro Fuentes +1
Deep learning has been achieving decent performance in computer vision requiring a large volume of images, however, collecting images is expensive and difficult in many scenarios.…