510 citations · 972 across the 24 of their papers we have counts for
5 papers · 1 filter
Efficient Convolutional Neural Network with Binary Quantization Layer
Mahdyar Ravanbakhsh, Hossein Mousavi, Moin Nabi +2
In this paper we introduce a novel method for segmentation that can benefit from general semantics of Convolutional Neural Network (CNN). Our segmentation proposes visually and sem…
Plug-and-Play CNN for Crowd Motion Analysis: An Application in Abnormal Event Detection
Mahdyar Ravanbakhsh, Moin Nabi, Hossein Mousavi +2
Most of the crowd abnormal event detection methods rely on complex hand-crafted features to represent the crowd motion and appearance. Convolutional Neural Networks (CNN) have show…
CNN-aware Binary Map for General Semantic Segmentation
Mahdyar Ravanbakhsh, Hossein Mousavi, Moin Nabi +2
In this paper we introduce a novel method for general semantic segmentation that can benefit from general semantics of Convolutional Neural Network (CNN). Our segmentation proposes…
Emotion-Based Crowd Representation for Abnormality Detection
Hamidreza Rabiee, Javad Haddadnia, Hossein Mousavi +3
In crowd behavior understanding, a model of crowd behavior need to be trained using the information extracted from video sequences. Since there is no ground-truth available in crow…
Self Paced Deep Learning for Weakly Supervised Object Detection
Enver Sangineto, Moin Nabi, Dubravko Culibrk +1
In a weakly-supervised scenario object detectors need to be trained using image-level annotation alone. Since bounding-box-level ground truth is not available, most of the solution…