3 citations · 7 across the 6 of their papers we have counts for
5 papers · 1 filter
Deep Metric Learning with Soft Orthogonal Proxies
Farshad Saberi-Movahed, Mohammad K. Ebrahimpour, Farid Saberi-Movahed +5
Deep Metric Learning (DML) models rely on strong representations and similarity-based measures with specific loss functions. Proxy-based losses have shown great performance compare…
Multi-Head Deep Metric Learning Using Global and Local Representations
Mohammad K. Ebrahimpour, Gang Qian, Allison Beach
Deep Metric Learning (DML) models often require strong local and global representations, however, effective integration of local and global features in DML model training is a chal…
Ventral-Dorsal Neural Networks: Object Detection via Selective Attention
Mohammad K. Ebrahimpour, Jiayun Li, Yen-Yun Yu +4
Deep Convolutional Neural Networks (CNNs) have been repeatedly proven to perform well on image classification tasks. Object detection methods, however, are still in need of signifi…
WW-Nets: Dual Neural Networks for Object Detection
Mohammad K. Ebrahimpour, J. Ben Falandays, Samuel Spevack +2
We propose a new deep convolutional neural network framework that uses object location knowledge implicit in network connection weights to guide selective attention in object detec…
Image captioning with weakly-supervised attention penalty
Jiayun Li, Mohammad K. Ebrahimpour, Azadeh Moghtaderi +1
Stories are essential for genealogy research since they can help build emotional connections with people. A lot of family stories are reserved in historical photos and albums. Rece…