Results 21 to 30 of about 41,227 (280)
Underwater Accompanying Robot Based on SSDLite Gesture Recognition
Applied Sciences, 2022 Underwater robots are often used in marine exploration and development to assist divers in underwater tasks. However, the underwater robots on the market have some problems, such as only a single function of object detection or tracking, the use of ...
Tingzhuang Liu +3 more
doaj +1 more source
Machines, 2022 Objective: We propose a deep-learning-based underwater target detection system that can effectively solve the problem of underwater optical image target detection and recognition. Methods: In this paper, based on the depth of the underwater optical image
Huilin Ge +3 more
doaj +1 more source
Competitive Deep-Belief Networks for Underwater Acoustic Target Recognition [PDF]
Sensors, 2018 Underwater acoustic target recognition based on ship-radiated noise belongs to the small-sample-size recognition problems. A competitive deep-belief network is proposed to learn features with more discriminative information from labeled and unlabeled samples.
Honghui Yang +4 more
openaire +2 more sources
Probabilistic Reconstruction of Color for Species’ Classification Underwater [PDF]
, 2015 Color is probably the most informative cue for object recognition and classification in natural scenes. Difference in shades can indicate to the biologist the potential for diversity of species or stress on the habitats. However, severe color distortions
Pe\u27eri, Shachak +2 more
core +2 more sources
Xibei Gongye Daxue Xuebao, 2020 As one of the main signal sources of underwater acoustic target recognition, the target noise signal is difficult to characterize the characteristics of the target from clearly comparing with the multi-sensor detection technology, which may lead to lower
doaj +1 more source
Underwater acoustic target recognition using attention-based deep neural network [PDF]
JASA Express Letters, 2021 Underwater acoustic target recognition based on ship-radiated noise is difficult owing to the complex marine environment and the interference by multiple targets. As an important technology for target recognition, deep-learning has high accuracy but poor interpretability.
Xu, Xiao +4 more
openaire +2 more sources
Journal of Marine Science and Engineering, 2022 In order to deal with the target recognition in the complex underwater environment, we carried out experimental research. This includes filtering noise in the feature extraction stage of underwater images rich in noise, or with complex backgrounds, and ...
Junyi Yang +3 more
doaj +1 more source
Deep convolution stack for waveform in underwater acoustic target recognition [PDF]
Scientific Reports, 2021 AbstractIn underwater acoustic target recognition, deep learning methods have been proved to be effective on recognizing original signal waveform. Previous methods often utilize large convolutional kernels to extract features at the beginning of neural networks. It leads to a lack of depth and structural imbalance of networks.
Shengzhao Tian +3 more
openaire +3 more sources
ARTMAP-FTR: A Neural Network For Fusion Target Recognition, With Application To Sonar Classification [PDF]
, 1998 ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include automatic mapping from satellite remote sensing data, machine tool monitoring, medical prediction ...
Carpenter, Gail A. +2 more
core +2 more sources
Real-time Model-based Image Color Correction for Underwater Robots
, 2020 Recently, a new underwater imaging formation model presented that the coefficients related to the direct and backscatter transmission signals are dependent on the type of water, camera specifications, water depth, and imaging range.
Li, Alberto Quattrini, Roznere, Monika
core +1 more source