Sökning: "siamese"

Visar resultat 1 - 5 av 33 uppsatser innehållade ordet siamese.

1. 1. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Khalid El Yaacoub; [2024]
   Nyckelord :Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

   Sammanfattning : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. LÄS MER

3. 2. Privacy Preserving Biometric Multi-factor Authentication

   Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

   Författare :Emil Gedenryd; [2023]
   Nyckelord :Fully Homomorphic Encryption; Machine Learning; Biometric Authentication; Technology and Engineering;

   Sammanfattning : This thesis investigates the viability of using Fully Homomorphic Encryption and Machine Learning to construct a privacy-preserving biometric multi-factor authentication system. The system is based on the architecture described as ”Model K - Store distributed, compare distributed” in ISO/IEC 24745:2022 and uses the Torus Fully Homomorphic Encryption scheme proposed by Chillotti et al. LÄS MER

4. 3. A Bidirectional ApproachApplied on Deeper and WiderSiamese Network

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Tobias Arnehall Johansson; [2023]
   Nyckelord :;

   Sammanfattning : Object tracking and object detection are two components within computer vision that have been widely improved during the last decade, in terms of precision and speed. This is mainly because deep learning has been incorporatedinto the algorithms, but also because new techniques and insights within the area are frequently released. LÄS MER

5. 4. Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcity

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

   Författare :David Brunell; [2022]
   Nyckelord :Siamese network; convolutional neural network;

   Sammanfattning : Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. LÄS MER

7. 5. Duplicate detection of multimodal and domain-specific trouble reports when having few samples : An evaluation of models using natural language processing, machine learning, and Siamese networks pre-trained on automatically labeled data

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Viktor Karlstrand; [2022]
   Nyckelord :Duplicate detection; Bug reports; Trouble reports; Natural language processing; Information retrieval; Machine learning; Siamese neural network; Transformers; Automated data labeling; Shapley values; Dubblettdetektering; Felrapporter; Buggrapporter; Naturlig språkbehandling; Informationssökning; Maskininlärning; Siamesiska neurala nätverk; Transformatorer; Automatiserad datamärkning; Shapley-värden;

   Sammanfattning : Trouble and bug reports are essential in software maintenance and for identifying faults—a challenging and time-consuming task. In cases when the fault and reports are similar or identical to previous and already resolved ones, the effort can be reduced significantly making the prospect of automatically detecting duplicates very compelling. LÄS MER