There is a trade-off between accuracy and efficiency in selecting the number of PBFICs: the...doi:10.1016/b978-0-12-811318-9.00021-1Ammar MahmoodMohammed BennamounFerdous SohelSenjian AnRobert B. Fisher
,“Deep Learning for Coral Classification,” in Handbook of Neural Computation, Elsevier Inc., 2017, pp. 383–401. Bengio, Y. Practical Recommendations for Gradient-Based Training of Deep Architectures 437–478 (Springer, 2012). Google Scholar A. D. Torres, H. Yan, A. H. Aboutalebi, A...
et al.: Deep Learning for Coral Classification. In: Handbook of Neural Computation, Elsevier Inc., pp. 383–401. (2017). https://doi.org/10.1016/B978-0-12-811318-9.00021-1 Anari, S., Tataei Sarshar, N., Mahjoori, N., Dorosti, S., Rezaie, A.: Review of deep learning ...
Deep Learning for Coral Classification Ammar Mahmood, ... Robert B. Fisher, in Handbook of Neural Computation, 2017 21.4 Deep Neural Networks An excellent performance of any image or video processing task (e.g., classification, object detection, scene understating) relies on the extraction of di...
We produced a large dataset of over 5,000 coral images that were classified into 11 species in the present automated deep learning classification scheme. We demonstrate the efficiency and reliability of the method, as compared to painstaking manual classification. Specifically, we demonstrated that ...
We present an efficient sparse classification for coral species using supervised deep learning method called Convolutional Neural Networks (CNNs). We compute Weber Local Descriptor (WLD), Phase Congruency (PC), and Zero Component Analysis (ZCA) Whitening to extract shape and texture feature ...
Deep Learning for Multilabel Classification of Coral Reef Conditions in the Indo‐Pacific Using Underwater Photo Transect Method Because coral reef ecosystems face threats from human activities and climate change, coral reef conservation programmes are implemented worldwide. Monitori... X Shao,H Chen,...
Supervised learning The term paradigm in machine learning corresponds to the classification of learning methods based on the input data and task37. Supervised learning utilizes labeled data to train a model to accurately predict the labels in the training set, whereas unsupervised learning trains a mo...
deep learningdata augmentationAdam optimisationCNNclassificationClassifying underwater photos representing coral benthic cover is a major challenge for marine ... RJ Firdous,S Sabena - 《Journal of Environmental Protection & Ecology》 被引量: 0发表: 2023年 Culture-Independent Raman Spectroscopic Identificati...
First, several deep learning models are utilized to extract useful information from multiple modalities. Among these are pre-trained Convolutional Neural Networks (CNNs) for visual and audio feature extraction and a word embedding model for textual analysis. Then, a novel fusion technique is proposed...