Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
Kamila Abdiyeva
Affiliation
SEDS, Nazarbayev University, Kazakhstan
EEE, NTU, Singapore
EEE, NTU, Singapore
Topic
Convolutional Neural Network,Neural Network,Bitwise Operations,Convolutional Layers,Graphics Processing Unit,MNIST Dataset,Action Classes,Action Recognition,Architectural Modifications,Arithmetic Operations,Artificial Neural Network,Attention Mechanism,Bayesian Model,Binary Convolutional Neural Network,Binary Image,Binary Model,Binary Network,Body Parts,Boolean Function,Bounding Box,Center Of Mass,Co-occurrence Matrix,Co-occurrence Statistics,Coherent State,Color Channels,Color Images,Combination Of Segmentation,Computational Complexity,Computational Elements,Computer Technology,Computer Vision,Computer Vision Area,Connection Weights,Contextual Information,Conv Layer,Conventional Convolutional Neural Networks,Convolution Output,Convolutional Network,Convolutional Neural Network Algorithm,Convolutional Neural Network Model,Drastic Drop,Entangled State,Error Gradient,Feature Maps,Feed-forward Network,Filter Size,First Set Of Experiments,Global Attention,Global Context,Global Context Information,
Biography
Kamila Abdiyeva received the B.Eng. degree in computer science from Nazarbayev University, Kazakhstan, in 2015. She is currently pursuing the Ph.D. degree with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Her research interests include computer vision, machine learning, and deep learning.