Computer vision models in intelligent aquaculture with emphasis on fish detection and behavior analysis: a review
Intelligence technologies play an important role in increasing product quality and production
efficiency in digital aquaculture. Automatic fish detection will contribute to achieving …
efficiency in digital aquaculture. Automatic fish detection will contribute to achieving …
A survey of recent advances in cnn-based single image crowd counting and density estimation
VA Sindagi, VM Patel - Pattern Recognition Letters, 2018 - Elsevier
Estimating count and density maps from crowd images has a wide range of applications
such as video surveillance, traffic monitoring, public safety and urban planning. In addition …
such as video surveillance, traffic monitoring, public safety and urban planning. In addition …
Generating high-quality crowd density maps using contextual pyramid cnns
VA Sindagi, VM Patel - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
We present a novel method called Contextual Pyramid CNN (CP-CNN) for generating high-
quality crowd density and count estimation by explicitly incorporating global and local …
quality crowd density and count estimation by explicitly incorporating global and local …
Jhu-crowd++: Large-scale crowd counting dataset and a benchmark method
We introduce a new large scale unconstrained crowd counting dataset (JHU-CROWD++)
that contains “4,372” images with “1.51 million” annotations. In comparison to existing …
that contains “4,372” images with “1.51 million” annotations. In comparison to existing …
Deep count: fruit counting based on deep simulated learning
M Rahnemoonfar, C Sheppard - Sensors, 2017 - mdpi.com
Recent years have witnessed significant advancement in computer vision research based
on deep learning. Success of these tasks largely depends on the availability of a large …
on deep learning. Success of these tasks largely depends on the availability of a large …
Cnn-based density estimation and crowd counting: A survey
Accurately estimating the number of objects in a single image is a challenging yet
meaningful task and has been applied in many applications such as urban planning and …
meaningful task and has been applied in many applications such as urban planning and …
Multi-level bottom-top and top-bottom feature fusion for crowd counting
VA Sindagi, VM Patel - Proceedings of the IEEE/CVF …, 2019 - openaccess.thecvf.com
Crowd counting presents enormous challenges in the form of large variation in scales within
images and across the dataset. These issues are further exacerbated in highly congested …
images and across the dataset. These issues are further exacerbated in highly congested …
A large contextual dataset for classification, detection and counting of cars with deep learning
TN Mundhenk, G Konjevod, WA Sakla… - Computer Vision–ECCV …, 2016 - Springer
We have created a large diverse set of cars from overhead images (Data sets, annotations,
networks and scripts are available from http://gdo-datasci. ucllnl. org/cowc/), which are useful …
networks and scripts are available from http://gdo-datasci. ucllnl. org/cowc/), which are useful …
A survey of crowd counting and density estimation based on convolutional neural network
Crowd counting and crowd density estimation methods are of great significance in the field
of public security. Estimating crowd density and counting from single image or video frame …
of public security. Estimating crowd density and counting from single image or video frame …
A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for
human consumption and environmental protection. Deep Learning methods have shown …
human consumption and environmental protection. Deep Learning methods have shown …