[PDF] Top 20 Individual minke whale recognition using deep learning convolutional neural networks

... For minke whales, photo-ID has typically involved visual comparison of large numbers of photographsby trained researchers; thus, the process is ...dwarf minke whales in re- cent years has come from tourists ... See full document

... level neural networks that was developed for ...abstraction. Deep learning and its development have been greatly facilitated by the use of GPUs (Graphics Processing ...a neural network, ... See full document

... level neural networks that was developed for ...abstraction. Deep learning and its development have been greatly facilitated by the use of GPUs (Graphics Processing ...a neural network, ... See full document

... vehicle recognition and classifica- tion is ...the deep learning model is ...experiments using the developed vision system to process closed-circuit television (CCTV) video data under varying ... See full document

... Disease, Deep Learning, Convolutional Neural Network, Pooling layer, Le-Net, Convolutional layer, Activation, ReLu, Plants etc ...any individual wants to know which type of ... See full document

... DCNN. Using the concept of transfer learning, it was only necessary to replace the last FC layer and to fine tune the weight parameters of each layer by using the RCF defect ...transfer ... See full document

... optimized using backpropagation, it is an excellent deep learning architecture that produces minimal prediction error ...works using DCNNs have focused on using visual data from video ... See full document

... optimal learning model ...sizes, learning rates, dropout probabilities, number of nodes in the fully connected layer, and the number of CNN layers for feature ... See full document

... Fast Learning Strategy Strategy for speeding up and stabilizing neural network training are considered in this paper, including batch learning, momentum and weight ...batch learning strategy ... See full document

... improved using deep ...and deep learning to build a system that uses different feature extraction algorithms, namely PCA, LBP+PCA, and LBP+NN, to ensure that each classifier produces its own ... See full document

... Machine learning algorithms combined with artificial intelligence techniques have been developed in order to detect expressions found in multimedia elements, including videos and ...of Deep Learning ... See full document

... digit recognition is gaining a huge demand in the branch of computer ...called Convolutional network is taken into consideration. A Convolutional network has a benefit over other Artificial ... See full document

... emotion recognition is inherently a multimodal ...of deep learning models with greater control compared with using daily-life ...of convolutional neural networks in ... See full document

... digit recognition becomes vital scope and it is appealing many researchers because of its using in variety of machine learning and computer vision ...of using Arabic digits endeavours us to ... See full document

... Keywords: convolutional neural network, deep learning, gesture recog- nition, sign language recognition 1 Introduction Very few people understand sign ... See full document

... of Deep Convolutional Neural Networks (DCNN) have dramatically advanced challenging computer vision tasks, especially in object detection and object clas- sification, achieving ... See full document

... transformations using deep feature ...to learning image ...pre-trained networks and has the ability to run on much higher resolution im- ...generative networks are distinct from our ... See full document

... Konvolucijsko nevronsko mreˇ zo smo uˇ cili prepoznavanja prometnih znakov na German traffic sign recognition base (GTSRB) [24] (slika 4.1) ter na Bel- gium Traffic Sign Dataset for Clas[r] ... See full document

... Python Deep Learning Library Keras is a high-level deep learning library implemented in Python that works on top of existing other rather low-level deep learning frameworks like ... See full document

... architecture convolutional neu- ral network achieves better accuracy than the state-of-the-art methods, the intensity nor- malization procedure and the neutral subtraction procedure achieves, respectively, ... See full document