MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for
Efficient Object Detection

MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection

26 November 2021

Hao Li

Papers citing "MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection"

8 / 8 papers shown

Title
Underwater object detection in sonar imagery with detection transformer and Zero-shot neural architecture search XiaoTong Gu Shengyu Tang Yiming Cao Changdong Yu ViT 29 0 0 10 May 2025
Merino: Entropy-driven Design for Generative Language Models on IoT Devices Youpeng Zhao Ming Lin Huadong Tang Qiang Wu Jun Wang 77 0 0 28 Jan 2025
ZiCo-BC: A Bias Corrected Zero-Shot NAS for Vision Tasks Kartikeya Bhardwaj Hsin-Pai Cheng Sweta Priyadarshi Zhuojing Li 19 1 0 26 Sep 2023
DynamicDet: A Unified Dynamic Architecture for Object Detection Zhi-Hao Lin Yongtao Wang Jinhe Zhang Xiaojie Chu ObjD 23 30 0 12 Apr 2023
DAMO-YOLO : A Report on Real-Time Object Detection Design Xianzhe Xu Yiqi Jiang Weihua Chen Yi-Li Huang Yuanhang Zhang Xiuyu Sun ObjD 23 160 0 23 Nov 2022
DS-Net++: Dynamic Weight Slicing for Efficient Inference in CNNs and Transformers Changlin Li Guangrun Wang Bing Wang Xiaodan Liang Zhihui Li Xiaojun Chang 27 9 0 21 Sep 2021
SCNet: Training Inference Sample Consistency for Instance Segmentation Thang Vu Haeyong Kang Chang-Dong Yoo ISeg 57 90 0 18 Dec 2020
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,216 0 16 Nov 2016