Results 31 to 40 of about 27,149 (269)
Exploring Recurrent Neural Networks for On-Line Handwritten Signature Biometrics
IEEE Access, 2018 Systems based on deep neural networks have made a breakthrough in many different pattern recognition tasks. However, the use of these systems with traditional architectures seems not to work properly when the amount of training data is scarce.
Ruben Tolosana +3 more
doaj +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
Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences [PDF]
, 2015 With the rapid proliferation of smart mobile devices, users now take millions of photos every day. These include large numbers of clothing and accessory images.
Bala, Kavita +5 more
core +2 more sources
Enhancing Text Similarity Measurement with Hybrid Siamese Neural Networks and Lexical Features [PDF]
Advances in Engineering and Intelligence SystemsAccurately measuring text similarity holds significant importance in various text-centric applications, including text clustering, information retrieval, and question/answer systems.
Bei Zhou
doaj +1 more source
Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network
IEEE Access, 2022 Dairy cow face recognition using Neural Networks has several hurdles. For example, there are only a few instances of each individual. The positions and angles of the individuals in the image fluctuate considerably, the differences between individuals are
Feng Xu, Jing Gao, Xin Pan
doaj +1 more source
SNS-CF: Siamese Network with Spatially Semantic Correlation Features for Object Tracking
Sensors, 2020 Recent advances in object tracking based on deep Siamese networks shifted the attention away from correlation filters. However, the Siamese network alone does not have as high accuracy as state-of-the-art correlation filter-based trackers, whereas ...
Thierry Ntwari +3 more
doaj +1 more source
Developing a Siamese Network for Intrusion Detection Systems [PDF]
Proceedings of the 1st Workshop on Machine Learning and Systems, 2021 Machine Learning (ML) for developing Intrusion Detection Systems (IDS) is a fast-evolving research area that has many unsolved domain challenges. Current IDS models face two challenges that limit their performance and robustness. Firstly, they require large datasets to train and their performance is highly dependent on the dataset size.
Hanan Hindy +4 more
openaire +3 more sources
Siamese Instance Search for Tracking [PDF]
, 2016 In this paper we present a tracker, which is radically different from state-of-the-art trackers: we apply no model updating, no occlusion detection, no combination of trackers, no geometric matching, and still deliver state-of-the-art tracking ...
Gavves, Efstratios +2 more
core +2 more sources
Siamese Network for Fake Item Detection. [PDF]
, 2023 Currently, most multimedia users choose to purchase items through e-commerce. Nevertheless, one of the main concerns of online shopping is the possibility of obtaining counterfeit products. Therefore, it is crucial to monitor the product's authenticity, thus adopting an automatic mechanism to validate the similarity between the purchased item and the ...
Erica Coppolillo +5 more
openaire +2 more sources
Siamese networks for generating adversarial examples
CoRR, 2018 Machine learning models are vulnerable to adversarial examples. An adversary modifies the input data such that humans still assign the same label, however, machine learning models misclassify it. Previous approaches in the literature demonstrated that adversarial examples can even be generated for the remotely hosted model.
Mandar Kulkarni, Aria Abubakar
openaire +2 more sources