Search
Author
- Baosheng, Yu (1)
- Jianping, Gou (1)
- Khan, Muhammad Owais (1)
- Klamerus-Iwan, Anna (1)
- next >
Subject
- CUB200-2011 (1)
- SCGs (1)
Date issued
- 2023 (2)
Has File(s)
- true (2)
Search Results
Knowledge distillation is a simple yet effective technique for deep model compression, which aims to transfer the knowledge learned by a large teacher model to a small student model. To mimic how the teacher teaches the student, existing knowledge distillation methods mainly adapt an unidirectional knowledge transfer, where the knowledge extracted from different intermedicate layers of the teacher model is used to guide the student model. However, it turns out that the students can learn more effectively through multi-stage learning with a self-reflection in the real-world education scenario, which is nevertheless ignored by current knowledge distillation methods. Inspired by this, we devise a new knowledge distillation framework entitled multi-target knowledge distillation via stud... |
Natural and human activities have deteriorated urban soil’s health and ecological functions as compared to forest soils. Therefore, we hypothesized that any intervention in poor quality soil in urban area will change their chemical and water retention properties. The experiment was conducted in Krakow (Poland) in completely randomized design (CRD). The soil amendments used in this experiment consisted of control, spent coffee grounds (SCGs), salt, and sand (1 and 2 t ha−1) in order to evaluate the impact of these soil amendments on the urban soil chemical and hydrological properties. Soil samples were collected after 3 months of soil application. The soil pH, soil acidity (me/100 g), electrical conductivity (mS/cm), total carbon (%), CO2 emission (g m−2 day−1), and total nitrogen (%... |
