Results 21 to 30 of about 695,054 (265)
Remote Sensing, 2021 Hyperspectral image classification is essential for satellite Internet of Things (IoT) to build a large scale land-cover surveillance system. After acquiring real-time land-cover information, the edge of the network transmits all the hyperspectral images
Ning Lv +6 more
doaj +1 more source
Integrating deep features for material recognition [PDF]
2016 23rd International Conference on Pattern Recognition (ICPR), 2016 We propose a method for integration of features extracted using deep representations of Convolutional Neural Networks (CNNs) each of which is learned using a different image dataset of objects and materials for material recognition. Given a set of representations of multiple pre-trained CNNs, we first compute activations of features using the ...
Yan Zhang 0055 +3 more
openaire +2 more sources
A New Deep CNN Model for Environmental Sound Classification
IEEE Access, 2020 Cognitive prediction in the complicated and active environments is of great importance role in artificial learning. Classification accuracy of sound events has a robust relation with the feature extraction.
Fatih Demir +2 more
doaj +1 more source
Diagnostics, 2021 Manual diagnosis of skin cancer is time-consuming and expensive; therefore, it is essential to develop automated diagnostics methods with the ability to classify multiclass skin lesions with greater accuracy.
Muhammad Attique Khan +4 more
doaj +1 more source
SiamMixer: A Lightweight and Hardware-Friendly Visual Object-Tracking Network
Sensors, 2022 Siamese networks have been extensively studied in recent years. Most of the previous research focuses on improving accuracy, while merely a few recognize the necessity of reducing parameter redundancy and computation load. Even less work has been done to
Li Cheng +6 more
doaj +1 more source
Deep Private-Feature Extraction
CoRR, 2018 We present and evaluate Deep Private-Feature Extractor (DPFE), a deep model which is trained and evaluated based on information theoretic constraints. Using the selective exchange of information between a user's device and a service provider, DPFE enables the user to prevent certain sensitive information from being shared with a service provider, while
Seyed Ali Osia +5 more
openaire +3 more sources
Learning Objectness Transfer Networks for Visual Tracking
IEEE Access, 2019 Existing deep trackers mainly use deep neural networks pre-trained on the object recognition training sets to generate deep features as target representation.
Shi Pu, Kaili Zhao, Honggang Zhang
doaj +1 more source
Diagnostics, 2021 Radiogenomic and radiotranscriptomic studies have the potential to pave the way for a holistic decision support system built on genomics, transcriptomics, radiomics, deep features and clinical parameters to assess treatment evaluation and care planning ...
Eleftherios Trivizakis +3 more
doaj +1 more source
Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition
Sensors, 2019 The recognition performance of visual recognition systems is highly dependent on extracting and representing the discriminative characteristics of image data.
Hammam Alshazly +3 more
doaj +1 more source
Pulmonary Nodule Classification Using Feature and Ensemble Learning-Based Fusion Techniques
IEEE Access, 2021 The Pulmonary nodule indicates the presence of lung cancer. The deep convolutional neural networks (DCNNs) have been widely used to classify the pulmonary nodule as benign or malignant. However, an individual learner usually performs unsatisfactorily due
Muhammad Muzammil +4 more
doaj +1 more source