Object detection for crabs in top-view seabed imagery

05/02/2021

∙

This report presents the application of object detection on a database of underwater images of different species of crabs, as well as aerial images of sea lions and finally the Pascal VOC dataset. The model is an end-to-end object detection neural network based on a convolutional network base and a Long Short-Term Memory detector.

READ FULL TEXT

Object detection for crabs in top-view seabed imagery

Research Progress of Convolutional Neural Network and its Application in Object Detection

Probabilistic Model of Object Detection Based on Convolutional Neural Network

Optimizing ship detection efficiency in SAR images

Autonomous Underwater Vehicle: Electronics and Software Implementation of the Proton AUV

S-Extension Patch: A simple and efficient way to extend an object detection model

Object Detection, Recognition, Deep Learning, and the Universal Law of Generalization

Automated Vehicle Parking Occupancy Detection in Real-Time

Object detection for crabs in top-view seabed imagery

Related Research

Research Progress of Convolutional Neural Network and its Application in Object Detection

Probabilistic Model of Object Detection Based on Convolutional Neural Network

Optimizing ship detection efficiency in SAR images

Autonomous Underwater Vehicle: Electronics and Software Implementation of the Proton AUV

S-Extension Patch: A simple and efficient way to extend an object detection model

Object Detection, Recognition, Deep Learning, and the Universal Law of Generalization

Automated Vehicle Parking Occupancy Detection in Real-Time