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Optimized Loss Functions for Object detection: A Case Study on Nighttime
  Vehicle Detection

Optimized Loss Functions for Object detection: A Case Study on Nighttime Vehicle Detection

11 November 2020
Shang Jiang
Haoran Qin
Binglin Zhang
Jieyu Zheng
ArXivPDFHTML

Papers citing "Optimized Loss Functions for Object detection: A Case Study on Nighttime Vehicle Detection"

3 / 3 papers shown
Title
Greybox XAI: a Neural-Symbolic learning framework to produce
  interpretable predictions for image classification
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification
Adrien Bennetot
Gianni Franchi
Javier Del Ser
Raja Chatila
Natalia Díaz Rodríguez
AAML
25
29
0
26 Sep 2022
PP-YOLO: An Effective and Efficient Implementation of Object Detector
PP-YOLO: An Effective and Efficient Implementation of Object Detector
Xiang Long
Kaipeng Deng
Guanzhong Wang
Yan Zhang
Qingqing Dang
...
Hui Shen
Jianguo Ren
Shumin Han
Errui Ding
Shilei Wen
ObjD
48
275
0
23 Jul 2020
CBNet: A Novel Composite Backbone Network Architecture for Object
  Detection
CBNet: A Novel Composite Backbone Network Architecture for Object Detection
Yudong Liu
Yongtao Wang
Siwei Wang
Tingting Liang
Qijie Zhao
Zhi Tang
Haibin Ling
ObjD
207
244
0
09 Sep 2019
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