Results 31 to 40 of about 21,191 (172)
, 2021 This work addresses the problem of vehicle identification through non-overlapping cameras. As our main contribution, we introduce a novel dataset for vehicle identification, called Vehicle-Rear, that contains more than three hours of high-resolution ...
de Oliveira, Icaro O. +4 more
core +1 more source
Deep constrained siamese hash coding network and load-balanced locality-sensitive hashing for near duplicate image detection [PDF]
, 2018 We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced Locality Sensitive Hashing (LSH) indexing.
Cai, Z. +5 more
core +1 more source
Remote Sensing, 2023 Ship classification using the synthetic aperture radar (SAR) images has a significant role in remote sensing applications. Aiming at the problems of excessive model parameters numbers and high energy consumption in the traditional deep learning methods ...
Xinqiao Jiang +3 more
doaj +1 more source
Few Shot Learning in Histopathological Images:Reducing the Need of Labeled Data on Biological Datasets [PDF]
, 2019 Although deep learning pathology diagnostic algorithms are proving comparable results with human experts in a wide variety of tasks, they still require a huge amount of well annotated data for training.
Belar, Oihana +7 more
core +1 more source
SSM-Net for Plants Disease Identification in Low Data Regime
, 2020 Plant disease detection is an essential factor in increasing agricultural production. Due to the difficulty of disease detection, farmers spray various pesticides on their crops to protect them, causing great harm to crop growth and food standards.
Jadon, Shruti
core +1 more source
Semantic Textual Similarity with Siamese Neural Networks
Proceedings - Natural Language Processing in a Deep Learning World, 2019 Calculating the Semantic Textual Similarity (STS) is an important research area in natural language processing which plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction.
Tharindu Ranasinghe +2 more
openaire +1 more source
Classification of Imagined Speech Using Siamese Neural Network [PDF]
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020 Imagined speech is spotlighted as a new trend in the brain-machine interface due to its application as an intuitive communication tool. However, previous studies have shown low classification performance, therefore its use in real-life is not feasible. In addition, no suitable method to analyze it has been found. Recently, deep learning algorithms have
Dong-Yeon Lee, Minji Lee, Seong-Whan Lee
openaire +2 more sources
Retrieval of Family Members Using Siamese Neural Network [PDF]
2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), 2020 Retrieval of family members in the wild aims at finding family members of the given subject in the dataset, which is useful in finding the lost children and analyzing the kinship. However, due to the diversity in age, gender, pose and illumination of the collected data, this task is always challenging.
Jun Yu 0001 +3 more
openaire +2 more sources
Host-Based Intrusion Detection Model Using Siamese Network
IEEE Access, 2021 As cyberattacks become more intelligent, the difficulty increases for traditional intrusion detection systems to detect advanced attacks that deviate from previously stored patterns. To solve this problem, a deep learning-based intrusion detection system
Daekyeong Park +4 more
doaj +1 more source
Research on few-shot power detection of siamese network based on improved RPN
Journal of Hebei University of Science and Technology, 2023 In order to solve the problems of difficulty, low efficiency, and insufficient data to support large-scale training in existing power system detection methods, a few-shot detection method based on siamese network was proposed.
Jun FENG +4 more
doaj +1 more source