[PDF] Top 20 DETECTION OF WHALES USING DEEP LEARNING METHODS AND NEURAL NETWORKS
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DETECTION OF WHALES USING DEEP LEARNING METHODS AND NEURAL NETWORKS
... machine learning for detection or classification of marine ...whale detection program [1, 2, 3, 4, 5] provides extensive information about whale detection a and its importance The data used ... See full document
6
Evaluation of different machine learning methods and deep learning convolutional neural networks for landslide detection
... use deep-learning methods and CNNs for landslide ...high detection accuracy for identifying landslide ...landslide detection from GF-1 images with four spectral bands and 8 m spatial ... See full document
21
NETWORK INTRUSION DETECTION USING DEEP NEURAL NETWORKS
... of deep learning to model high-dimensional features, and the authors do not study the performance of the model in the binary ...power, deep learning methods have blossomed rapidly, and ... See full document
9
Disease Detection of Plants using Deep Learning and Convolutional Neural Networks
... of using pesticides and the type of ecosystem they are ...on detection and classification of plant diseases based on symptoms of the diseases that shows signs on the leaves of the ...Convolution ... See full document
5
Diabetic Retinopathy Detection Using Neural Network
... retina methods features for example micro-aneurysms, bleedings, firm exudates, yarn angora acnes or venous ...cure. Deep neural networks devise lately existed efficaciously practical in ... See full document
5
Biosignals learning and synthesis using deep neural networks
... or using delayed harmonic waves ...machine learning methods, one can synthesize signals by exploiting its predic- tion ...generated using dynamic time warp- ing [10], hidden Markov models ... See full document
17
Deep Machine Learning In Neural Networks
... reinforcement learning algorithm for scheduling. And this scheduling, using this algorithm when the problem occurs in distributed ...machine learning algorithm obtains heterogeneity of the nodes, and ... See full document
8
Deep Learning Techniques for Object Detection
... one-stage networks in order to maintain accuracy while eliminating ...Object Detection pertaining to motion-blur and de-focus, target ambiguity in video frames, occlusions and truncations etc, which is ... See full document
8
Deep Learning and Sociophonetics: Automatic Coding of Rhoticity Using Neural Networks
... extraction methods are widely available for vowels (Rosenfelder et ...automated methods for coding rhoticity have lagged far ...automated methods be developed to aid in coding rhoticity? In this ... See full document
5
NILC at CWI 2018: Exploring Feature Engineering and Feature Learning
... method using lexical, n-gram and psycholin- guistic features, (ii) a shallow neural network method using only word embeddings, and (iii) a Long Short-Term Memory (LSTM) language model, which is ... See full document
6
Cancer Classification using Principal Component Analysis and Deep Neural Networks
... by using some of the parameter plays very important role to reveal useful awareness of cancer ...machine learning model for cancer detection were used which is known as Principal Component Analysis ... See full document
10
Edge AI System for Pneumonia and Lung Cancer Detection
... The deep learning algorithms have presented a promising alternative to computer vision ...of deep learning algorithms are automatic training and learning using context/problem ... See full document
8
UAV based slope failure detection using deep learning convolutional neural networks
... the detection of slope failure is therefore an important topic for ...the methods currently used for mapping and modelling slope failures rely on classification algorithms or feature extraction, but the ... See full document
24
Multi-modal learning using deep neural networks
... of deep neural networks has enabled us to develop algorithms which give machines the ability to understand and interpret this ...Convolutional Neural Networks (CNN) have become a ... See full document
70
Individual minke whale recognition using deep learning convolutional neural networks
... minke whales ( Balaenoptera acutorostrata subsp ...individual whales is required for research on the whales’ population characteristics and for monitoring the potential impacts of tourism activities, ... See full document
12
Recent Advances in Anomaly Detection Methods applied to Aviation
... Anomaly detection is an active area of research with numerous methods and ...anomaly detection techniques and their application to the the aviation ...data-driven methods for anomaly ... See full document
27
Deep Learning as a Frontier of Machine Learning: A Review
... Deep neural network is a variant of multilayer feed-forward artificial neural ...of using extra hidden layers in the network enables the composition of features from lower ...the deep ... See full document
9
Deep Belief Networks Using Convolution Neural Networks Algorithm
... the learning algorithm. Moreover, it is important to tune the learning rates correctly for the different parameters W, b and ...optimization methods are ...it using the KL ... See full document
8
Machine Learning and Deep Learning
... machine learning and deep learning are roots of ...machine learning if any kind of analysis is to be ...machine learning from the ...on Deep Learning. Deep ... See full document
5
Fully automated, deep learning segmentation of oxygen-induced retinopathy images
... inspection, deep learning appeared to generate segmentations that look very similar to human segmentations for neo- vascular complexes (Figure 5), and machine learning generated much more precise ... See full document
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