Survey on deep learning for radiotherapy
More than 50% of cancer patients are treated with radiotherapy, either exclusively or in
combination with other methods. The planning and delivery of radiotherapy treatment is a …
combination with other methods. The planning and delivery of radiotherapy treatment is a …
Large-scale retrieval for medical image analytics: A comprehensive review
Over the past decades, medical image analytics was greatly facilitated by the explosion of
digital imaging techniques, where huge amounts of medical images were produced with …
digital imaging techniques, where huge amounts of medical images were produced with …
Speech emotion recognition using deep 1D & 2D CNN LSTM networks
We aimed at learning deep emotion features to recognize speech emotion. Two
convolutional neural network and long short-term memory (CNN LSTM) networks, one 1D …
convolutional neural network and long short-term memory (CNN LSTM) networks, one 1D …
Convolutional neural networks for intra-hour solar forecasting based on sky image sequences
Accurate and timely solar forecasts play an increasingly critical role in power systems.
Compared to longer forecasting timescales, very short-term solar forecasting has lagged …
Compared to longer forecasting timescales, very short-term solar forecasting has lagged …
A deep-learning-based approach for fast and robust steel surface defects classification
Automatic visual recognition of steel surface defects provides critical functionality to facilitate
quality control of steel strip production. In this paper, we present a compact yet effective …
quality control of steel strip production. In this paper, we present a compact yet effective …
DeepThin: A novel lightweight CNN architecture for traffic sign recognition without GPU requirements
For a safe and automated vehicle driving application, it is a prerequisite to have a robust and
highly accurate traffic sign detection system. In this paper, we proposed a novel energy …
highly accurate traffic sign detection system. In this paper, we proposed a novel energy …
MFF-SAug: Multi feature fusion with spectrogram augmentation of speech emotion recognition using convolution neural network
S Jothimani, K Premalatha - Chaos, Solitons & Fractals, 2022 - Elsevier
Abstract The Speech Emotion Recognition (SER) is a complex task because of the feature
selections that reflect the emotion from the human speech. The SER plays a vital role and is …
selections that reflect the emotion from the human speech. The SER plays a vital role and is …
Deep phenotyping: deep learning for temporal phenotype/genotype classification
Background High resolution and high throughput genotype to phenotype studies in plants
are underway to accelerate breeding of climate ready crops. In the recent years, deep …
are underway to accelerate breeding of climate ready crops. In the recent years, deep …
Minimalistic CNN-based ensemble model for gender prediction from face images
Despite being extensively studied in the literature, the problem of gender recognition from
face images remains difficult when dealing with unconstrained images in a cross-dataset …
face images remains difficult when dealing with unconstrained images in a cross-dataset …
Appearance based pedestrians' gender recognition by employing stacked auto encoders in deep learning
Pedestrians' gender is a soft attribute which is useful in many areas of computer vision
including human robot interaction, intelligent surveillance and human behavior analysis …
including human robot interaction, intelligent surveillance and human behavior analysis …