Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Reciprocal teacher-student learning via forward and feedback knowledge distillation
Knowledge distillation (KD) is a prevalent model compression technique in deep learning,
aiming to leverage knowledge from a large teacher model to enhance the training of a …
aiming to leverage knowledge from a large teacher model to enhance the training of a …
Logit standardization in knowledge distillation
Abstract Knowledge distillation involves transferring soft labels from a teacher to a student
using a shared temperature-based softmax function. However the assumption of a shared …
using a shared temperature-based softmax function. However the assumption of a shared …
Good teachers explain: Explanation-enhanced knowledge distillation
Abstract Knowledge Distillation (KD) has proven effective for compressing large teacher
models into smaller student models. While it is well known that student models can achieve …
models into smaller student models. While it is well known that student models can achieve …
[HTML][HTML] A Survey on Knowledge Distillation: Recent Advancements
Deep learning has achieved notable success across academia, medicine, and industry. Its
ability to identify complex patterns in large-scale data and to manage millions of parameters …
ability to identify complex patterns in large-scale data and to manage millions of parameters …
Efficient crowd counting via dual knowledge distillation
Most researchers focus on designing accurate crowd counting models with heavy
parameters and computations but ignore the resource burden during the model deployment …
parameters and computations but ignore the resource burden during the model deployment …
Expanding and refining hybrid compressors for efficient object re-identification
Y **
G Yang, S Yu, H Yang, Z Nie, J Wang - Plos one, 2023 - journals.plos.org
Previous studies have shown that deep models are often over-parameterized, and this
parameter redundancy makes deep compression possible. The redundancy of model weight …
parameter redundancy makes deep compression possible. The redundancy of model weight …
[HTML][HTML] Monocular depth estimation from a fisheye camera based on knowledge distillation
Monocular depth estimation is a task aimed at predicting pixel-level distances from a single
RGB image. This task holds significance in various applications including autonomous …
RGB image. This task holds significance in various applications including autonomous …