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Machine vision–based herbicide applications relying on object detection or image classification deep convolutional neural networks (DCNNs) demand high memory and computational resources, resulting in lengthy inference times. To tackle these challenges, this study assessed the effectiveness of three teacher models, each trained on datasets of varying sizes, including D-20k (comprising 10,000 true-positive and true-negative images) and D-10k (comprising 5,000 true-positive and true-negative images). Additionally, knowledge distillation was performed on their corresponding student models across a range of temperature settings. After the process of student–teacher learning, the parameters of all student models were reduced. ResNet18 not only achieved higher accuracy (ACC ≥ 0.989) but also maintained higher frames per second (FPS ≥ 742.9) under its optimal temperature condition (T = 1). Overall, the results suggest that employing knowledge distillation in the machine vision models enabled accurate and reliable weed detection in turf while reducing the need for extensive computational resources, thereby facilitating real-time weed detection and contributing to the development of smart, machine vision–based sprayers.

China conducted a comprehensive overhaul of its environmental regulation as of April 2014. The regulation, which calls for a holistic approach to protect the environment, is also called the “Ecological Protection Red Line” (Red Line). It sets comprehensive standards for pollutants and mandates provinces to implement the regulations. The Porter and pollution haven hypotheses were tested for the impact of the Red Line on firm exports using a sample of Chinese A-share firms from 2011 to 2017. Our findings are consistent with the Porter hypothesis. The implementation of the Red Line has a positive impact on a firm’s exports. The findings are robust to alternative metrics of exports and different sub-samples. A firm’s innovation activities (in terms of research and development investments) and production efficiency were found to be the transmission channels, corroborating the underlying logic of the Porter hypothesis. Policy implications are discussed.